phd in information systems

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The School of Information is UC Berkeley’s newest professional school. Located in the center of campus, the I School is a graduate research and education community committed to expanding access to information and to improving its usability, reliability, and credibility while preserving security and privacy.

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The School of Information offers four degrees:

The Master of Information Management and Systems (MIMS) program educates information professionals to provide leadership for an information-driven world.

The Master of Information and Data Science (MIDS) is an online degree preparing data science professionals to solve real-world problems. The 5th Year MIDS program is a streamlined path to a MIDS degree for Cal undergraduates.

The Master of Information and Cybersecurity (MICS) is an online degree preparing cybersecurity leaders for complex cybersecurity challenges.

Our Ph.D. in Information Science is a research program for next-generation scholars of the information age.

• Fall 2024 Course Schedule

The School of Information's courses bridge the disciplines of information and computer science, design, social sciences, management, law, and policy. We welcome interest in our graduate-level Information classes from current UC Berkeley graduate and undergraduate students and community members.  More information about signing up for classes.

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Research by faculty members and doctoral students keeps the I School on the vanguard of contemporary information needs and solutions.

The I School is also home to several active centers and labs, including the Center for Long-Term Cybersecurity (CLTC) , the Center for Technology, Society & Policy , and the BioSENSE Lab .

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Ph.D. in Information Science

Ph.d. community.

Ph.D. students are knowledge architects and respected contributors to our information society, with a vision of expanding access to quality information, an appreciation for diverse perspectives, and the spirit of collaboration.

You Belong at Berkeley

The I School is a welcoming community of students, faculty, and staff from a wide variety of backgrounds, nations, cultures, and experiences.

The doctoral program is a research-oriented program in which the student chooses specific fields of specialization, prepares sufficiently in the literature and the research of those fields to pass a qualifying examination, and completes original research culminating in the written dissertation. The degree of Doctor of Philosophy is conferred in recognition of a candidate's grasp of a broad field of learning and distinguished accomplishment in that field through contribution of an original piece of research revealing high critical ability and powers of imagination and synthesis.

The Ideal Place for Breakthrough Thinking

School of Information offers an ideal environment for information scholars , on the campus of a preeminent, forward-thinking research institution .

Dedicated to cross-disciplinary research, breakthrough thinking, and creative collaboration, the I School actively shapes the information frontier and has a track record of scholarly ideas, solutions, and policy counsel that make information more accessible, manageable, and useful.

Rigorous academics instill the theoretical and research capabilities required to advance diverse interests — from information design, architecture, and assurance, to human-computer interaction and the social, economic, and public policy implications of information. Ph.D. students work closely with faculty recognized as information pioneers.

Interdisciplinary thinking and partnership are central to the I School approach, so doctoral research often engages exceptional UC Berkeley schools and departments beyond the I School, from journalism, business, and law to computing, engineering, humanities, and social sciences.

On average, I School students complete the Ph.D. degree in 6 years.

• Semester 1–4 : Breadth, major, & minor coursework
• Semester 4–5 : Prelim research paper & exam
• Semester 6–8 : Qualifying exam
• Semester 10–12 : Complete & present dissertation

Detailed degree requirements & timeline

Areas of Study

Major and minor areas include:

• Human-Computer Interaction
• Information Economics and Policy
• Information Law and Policy
• Information Organization and Retrieval
• Information Systems Design
• Social Aspects of Information
• Information and Communication Technologies and Development

Your Career

I School Ph.D. graduates go on to careers in academia, industry, or the public sector.

Recent Ph.D. graduates hold tenure-track faculty positions at the world’s leading universities, as well as leading research positions in industry, academia, and public-interest organizations.

More about Ph.D. career outcomes

“I think we can do a better job of using the Internet to tap into how people are doing, how they’re feeling, and what matters to them — online democracy, in a way, but minus the hype.”

—Galen Panger Ph.D. 2017

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Department of Technology, Operations, and Statistics | Doctoral Program in Information Systems

Doctoral program in information systems.

• Overview of the Doctoral Program in Information Systems

Program Requirements

Doctoral Courses

• Doctoral Students and their Research
• Information Systems Faculty

Overview of the IS Doctoral Program

Mission: To educate and train scholars who will produce first-rate IS research and who will succeed as faculty members in first-rate universities. We offer tracks in technical perspectives on IS, economic perspectives on IS, and organizational/management perspectives on IS. Admissions and performance: We enroll an average of three students each year out of more than 100 highly qualified applicants. Students enrolling typically have GMATS over 700 or GREs over 1400. International students typically have TOEFLs higher than 640. Our students are highly competitive within Stern and nationally. Recently our students have received school-wide awards as "outstanding doctoral students." They have won acceptance at doctoral consortia sponsored by the Academy of Management and the International Conference on Information Systems. And they have won national dissertation research competitions.

Advising and evaluation: The IS doctoral program faculty director advises all first-year doctoral students. During the first year students have many opportunities to get to know the research interests of all departmental faculty. By the beginning of the second year, students have selected a concentration advisor who will guide them through the comprehensive exam process and up to the thesis stage. By the middle of the third year students will have selected a thesis advisor. Each year every student submits a statement of intellectual progress to his/her advisor. All faculty meet to review the progress of all students in a day-long meeting each year. At this time, the student's intellectual progress is reviewed and plans for the following year are considered. The results of this review include a formal letter to the student assessing the previous year's work and offering guidance for the following year's work. All students take a comprehensive written and oral exam at the end of the second year. Students defend their thesis proposal by March of their fourth year and defend their completed dissertation at the end of the fourth year or during the fifth year.

Research and interaction with faculty: The heart of the IS doctoral program is immersion in a community of researchers. Every student has a formal research apprenticeship with one or more faculty members each year. Every student participates in formal and informal research seminars each week with departmental faculty and visitors. Every student presents research in progress and works toward producing publishable papers, usually with a faculty co-author. Students learn to be researchers by doing research. They learn to be research colleagues by working with others and critiquing their research.

Placement record: In the past ten years, our graduates have accepted faculty positions at such schools as University of California at Berkeley, Hong Kong University of Science & Technology, University of Maryland, University of Minnesota, University of Texas at Austin, the University of British Columbia, National University of Singapore, The Wharton School and the University of Cambridge, UK.   Please click on the links on the right to learn how to apply, to attend an information session, and to contact the Stern School Doctoral Office. 

Natalia Levina Coordinator, Information Systems Doctoral Program IOMS Department

Back-to-Top

All students take a common core of courses during their first year which provides an overview of the major research areas in IS and the fundamental knowledge necessary for specialized course work in the second year. In the second year students take specialized course work in one of three concentrations: technical perspectives, economic perspectives, behavioral/managerial perspectives.  

Mandatory Breadth Courses (3)

• Behavioral Research Methods
• Micro-economics
• Technical Foundations
• Each student is required to take 1 Probability and 1 Statistics course, from a list of approved courses.
• Technical Research in IS
• Economics Research in IS
• Behavioral/Managerial Research in IS
• Research Apprenticeship

YEAR TWO - Each student chooses one concentration track

Technical Track:

• A programming requirement, may be satisfied in a variety of ways
• Honors Analysis of Algorithms
• Artificial Intelligence
• Optimization
• Database Systems
• Machine Learning/Data Mining
• Other courses based on student's interest
• Research apprenticeship

Economics Track:

• Mathematical Methods for Economists
• Econometrics
• Game Theory
• Students will take elective courses in the Stern Economics Department, at the Graduate School of Arts and Sciences, in Operations Management, Statistics, or at Courant as specified in consultation with the advisor

Behavioral/Managerial Track:

• Any two of the following four Stern Management Department Courses
• Organizational Behavior
• Managerial Cognition
• Organizational Theory
• At least one research methods or statistics course beyond the first year courses.
• Students may take doctoral level courses in Psychology, Sociology, Political Science, Public Policy, History, Education, or Law.
• Electives in the area of interest
• Thesis research
• Teaching apprenticeship (in year 3 or 4)
• Teaching one course (in year 3 or 4)
• INFO-GB.3345 (B20.3345)  Doctoral Seminar in Digital Economics  (offered in Spr 2012) This course introduces students to scientific paradigms and research perspectives related to the economics of information technologies. Topics in 2012 include information goods, piracy, digital rights management, network economics, sponsored search auctions, user-generated content, contagion in networks, technological innovation, IT productivity, the digital commons and online privacy.  
• INFO-GB.3382 (B20.3382)  Research Seminar on IT and Organizations: Social Perspectives (offered in Spr 2012) The course introduces students to sociological and organizational literature on the role of Information Technology in organizations and society.  
• INFO-GB.3383 (B20.3383)  Networks, Crowds & Markets   
• INFO-GB.3386 (B20.3386)  Technical Foundations of IS  
• INFO-GB.3355 (B20.3355)  Behavioral Research Methods  
• INFO-GB.3391 (B20.3391)  Research Seminar in Data Science   (offered in Spr 2012) In this course we will take a deep dive into selected topics in data science. The focus will be two-fold. First, we will read textbook segments, classic papers, and new research, with the goal of understanding research in data science. Second, we will study the actual practical application of data science methods to extract knowledge from large-scale data. We will cover topics such as machine learning, data mining, information retrieval, text classification, sentiment analysis, similarity analysis, network analysis, graphical models, Bayesian models, topic models, model evaluation, crowd-sourcing and micro-outsourcing, massive-scale data processing, reducing data for analytic purposes, and more. The selection of which topics are covered in a particular semester will be based on: (i) the current research and business environments, (ii) the research interests of the IS faculty, and (iii) the interests of the students in that semester. We also will discuss applications that are of current interest, such as recommender systems, social-network marketing, online advertising, Mechanical Turking, and more.

Questions about the PhD Program in Information Systems?

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RESEARCH AT THE LEADING EDGE

Where You Get Your Ph.D. Matters. Get Yours at a Global Center of Innovation.

Ph.D. Studies at Heinz College

You have the vision. You have the drive. What you need now is a doctoral program that will challenge and support you on your path to a career as a researcher, educator, and expert.

Heinz College is a graduate school without boundaries.

Distinguished by the interdisciplinary model of Heinz College and Carnegie Mellon University, our Ph.D. programs prepare graduates to lead change in their chosen fields through meaningful collaborations and hands-on work with our renowned and extremely accessible faculty. 

Heinz College features the unique co-location of two schools: The School of Information Systems and Management and The School of Public Policy and Management; however, below that larger structure, we are a college without departments and their characteristic silos. Our faculty, students, and research centers thrive by working together to solve problems across subjects, disciplines, and business verticals.

In the Heinz Ph.D. program, you will conduct innovative research to address increasingly complex challenges facing society, whether those challenges are technical, organizational, political, economic, social, or—as is often the case—some combination thereof.

Heinz College Is The #1 Analytics Education Program And Has Been #1 In Information And Technology Management Since 2001

Decorated faculty & research centers, here, you will work with award-winning thought leaders and boundary-busting research centers.

Truly Interdisciplinary

Matthew Eisenberg chose Heinz College for his research for the promise of interdisciplinary collaboration—like bringing machine learning to health economics.

Recent Best Paper Awards From Our Faculty

Alessandro Acquisti — Management Science, Best Paper

George Chen —  AAAI Workshop on AI for Behavior Change, Best Paper

Akshaya Jha — United States Association for Energy Economics, Young Professional Research Award and Best Paper

Ramayya Krishnan & Beibei Li — Information Systems Research, Best Paper Finalist

Rema Padman — Association of Information Systems, SIGHealth section, Best Paper

Alessandro Acquisti —  Information Systems Research, Best Paper

Leman Akoglu —   SIAM International Conference on Data Mining (SDM), Best Paper

George Chen —  INFORMS Data Mining and Decisions Analytics Workshop, Best paper (theoretical track)

Beibei Li   — International Conference on Information Systems (ICIS), Best Paper

Beibei Li  —  Workshop on Information Technologies and Systems (WITS), Best Paper  

Ananya Sen  —  Workshop on Information Systems and Economics, Best Paper

Zhe Zhang  —  ACM, Best Doctoral Dissertation Runner-Up

Alessandro Acquisti  —  Management Information Systems Quarterly, Best Paper

Leman Akoglu  —  ECML PKDD, Best Paper

Martin Gaynor  —  National Institute of Health Care Management Research, Best Paper

Recent Ph.D. Accolades

David Adler  was selected as the 2019-2020 recipient of the Institute for Regulatory Law & Economics Graduate Fellowship.

Nate Breg was selected to receive one of the Center for Machine Learning and Health 2020 Fellowships in Digital Health .

Maria Caballero  was selected to participate in the Western Economic Association International’s Graduate Student Workshop, held at the association's  95th Annual Conference .

William Herlands  was named a finalist for the  Schmidt Science Fellows .  

Mikaela Meyer has been selected for the American Statistical Association’s 2020 Gertrude Cox Scholarship Award .

Ph.D. in Information Systems & Management

Gain a deep understanding of the technical and organizational aspects of information systems

Key research areas in Information Systems & Management include: Economics of Digitization | Machine Learning & Large-Scale Data Analytics | Information Security & Privacy | Health Care & IT

Ph.D. in Public Policy & Management

Apply a rigorous scientific approach to social, organizational, economic, and management problems in an increasingly connected world

Key research areas in Public Policy & Management include: Crime & Drug Policy | Energy & Environmental Policy | Health Economics & Policy | Labor Economics | Management Science

Joint Ph.D. Programs

Heinz College offers joint Public Policy Ph.D. programs in cooperation with other CMU departments

Explore joint degree programs with CMU’s Tepper School of Business, School of Computer Science, and the College of Engineering

Department of Information Systems

College of engineering and information technology, doctor of philosophy in information systems.

The Graduate School at UMBC is located in the heart of the Baltimore-Washington metropolitan area, a premier location known for its flourishing tech industry.

Our Ph.D. is one of the few programs that approaches Information Systems in a holistic sense, including the social and political elements of building and maintaining complex, large-scale systems. We have a diverse, multicultural faculty and student body that practices an interdisciplinary and applied approach to Information Systems.

Our well-renowned full-time faculty is involved with a wide variety of externally funded projects and they are also proudly featured in top scholarly venues.

Admission Requirements

•  The majority of successful applicants have an undergraduate GPA well above 3.0 (on a 4.0 scale).
• The IS Ph.D. program builds on an understanding of the design, development, analysis, and use of computer-based information systems. Successful applicants will have demonstrated aptitude and/or interest in one or more of these areas. In addition, applicants should have or be willing to acquire the necessary competence in some of the following areas depending on their research concentration: statistical analysis, experimental design, programming, databases and data mining, computational analysis, in order to conduct sophisticated research at the doctoral level.

We currently accept Test of English as a Foreign Language (TOEFL), IELTS (International English Language Testing System), and PTE Academic (Pearson Test of English). The minimum acceptable combined TOEFL score is 550 (written), 213 (computer based) or 80 (iBT-Internet based). The TOEFL code for UMBC is  5835 . For IELTS, the minimum acceptable total score is 6.5. A minimum score of 53 is required on the PTE Academic test. We will also accept Duolingo English test. The minimum required score is 115.

• GRE scores are optional: The IS department is multi-disciplinary with faculty of varied research interests. While the GRE is not required, it is an opportunity for you to demonstrate your capabilities. The importance of the GRE in the admissions process may vary substantially by subject area. Whether or not you submit the GREs, you are required to demonstrate analytical and writing skills as described in the second bullet in the SOP section.
• What research area are you interested in? Why would you like to work in that particular area?  What aspects of your background will prepare you to work in that area? What are your career goals? What prior experience do you have in conducting/assisting in research?
• You are required to demonstrate analytical and writing skills, for example, through GREs, industry experience, research experience, certifications, challenging professional or academic projects, coursework performance, papers or articles published, achievements in national or international contests, hackathons, and/or code/visualizations you have created. You can use additional documents to show evidence of some of these qualities.
• Also, look on the web for information about the professors and their research. Indicate which research area(s) you are interested in working in, perhaps commenting on the interdisciplinary nature of your interests.
• You are strongly encouraged to contact individual faculty members with whom you are interested in working and discuss with them about your background and interests.
• Three letters of recommendation
• Official transcripts of all post-secondary schools (Electronic Transcripts: If you are submitting transcripts electronically, please forward to Kathie Nee, [email protected], for domestic applications and to Scott Philips, [email protected],  for international applications.
• The UMBC Graduate School will accept official WES ICAP Course-by-Course evaluations as fulfillment of the requirement for official transcripts in the admissions process.

The deadlines for the Ph.D. program are:

• Fall semester: January 7
• Spring semester: September 1

All application materials must be submitted by the deadline. Only applications that are complete by the deadline, with all required documents, are considered. Upon request, incomplete applications will be kept open for the following semester’s admission decisions.

If you need any further information please contact Shannon Carey (Keegan), Graduate Programs Manager, [email protected] .

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• Programs : PhD in Information Studies

PhD in Information Studies

alt="Doctoral PhD students collaborating in the Information eXeprience Lab"

Where Grand Challenges Meet Interdisciplinary Solutions

We live in the Information Age, offering unprecedented opportunities but also unmatched threats and challenges. Information systems and technologies are fundamentally shaping the behaviors of individuals, organizations, and society. To understand the dynamics of our world, and to help shape a future that reflects social values, research at the School of Information crosses disciplinary divides, bridges the arts and the sciences, and applies human insights to technological advances.

Our flexible curriculum and immersive mentorship with  world-class faculty who are experts in their fields prepare students to become high-quality, high-impact researchers, scholars, and teachers. Throughout the doctoral program, students will learn to reason and evaluate ideas and data across disciplines, see beyond current approaches to problems, and cross disciplinary boundaries in search of answers to the grand challenges facing today's modern information society.

Join Our Community of Innovative Scholars

At the School of Information, you will work with faculty who are among the best in the world in their areas of expertise. You will be immersed in an environment that offers the facilities and resources of one of the premier research universities in the US, and live in a city that is both a rapidly growing center for IT research and development and one of the country's most vibrant cities in which to live and work.

Admissions & Funding

Learn about admissions procedures as well as funding available for doctoral students.

Program Overview

Our curriculum offers flexibility to tailor your coursework and explore research interests.

Meet Our Faculty

Over 20 full-time, world-class faculty come from diverse, interdisciplinary backgrounds.

Research at the iSchool

We're tackling the greatest challenges facing today's modern information society — how to understand the extraordinary complexity of information, to discover principles and processes for managing its massive scale, and exploring ways to leverage it to enhance our lives.

PhD Degree Requirements

• Committees & Annual Review
• Coursework & Plan of Study
• Qualifying Procedure
• Proposal & Dissertation Defense

What Do We Look For?

The study of information extends beyond any existing field. Our PhD students come from a wide range of disciplinary backgrounds, and we welcome applications from interested candidates regardless of the field of study in which you completed your prior degree(s). A master's degree is not required to apply. 

We seek the best and brightest people who thrive on challenges:

People dedicated to creating new forms of information systems that can augment human and organizational capabilities.

People committed to exploring the human and technological principles and processes that underlie information complexity.

People energized by a vision of a diverse society where access to relevant information is not a luxury, but a requirement.

People appreciative of the importance and challenge of preserving and disseminating information on the human cultural record.

If you want to join us in helping to forge a better information society:  Apply to the PhD Program

Our Vision & Values

The School of Information is committed to making a positive difference in people’s lives through excellence in research, teaching, and public engagement. Our core values underpin our efforts to shape the field of information for human and social benefit.

About The University of Texas at Austin

The University of Texas at Austin is one of the largest public universities in the US. Beyond our top-ranked international graduate program, UT Austin is one of the world's premier research universities and is located in one of the sunniest and most vibrant cities in which to live and work: Austin, TX.

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PhD in IS Program Flyer    Meet Current Students    Explore FAQs

PhD in Business Administration with a Specialization in Information Systems

You are here.

The Information Systems (IS) doctoral program is a research-based program where students work with world-renowned scholars to build skills that will prepare them for impactful careers as professors in information systems at business schools.

Overall, the doctoral program places a heavy emphasis on training students through active engagement in the research process. Students develop a strong foundation in research methods and statistics, while closely collaborating with multiple faculty members on research projects.

General details about the curriculum, requirements, and structure of the  program can be found here . Please be aware this document is not an exhaustive list of the requirements for the program.

Program Faculty

Our renowned, award-winning IS faculty are published experts on topics like:

Artificial Intelligence and Deep Learning

Cybersecurity, Text Analytics and Face Recognition

Emerging Digital Technologies

Large Language Models (LLMs)

Machine Learning and Semantic/Lexical Analytics

Natural Language Processing

Tools and Methods for Making Sense of Large Data

Jason Bennett Thatcher

Tandean Rustandy Esteemed Endowed Chair

David Dobolyi

Assistant Professor

Abram Handler

Associate Professor

Ramiro Montealegre

Assistant Professor • Information Analytics PhD Program Director

Program Graduates

The PhD program prepares students to be researchers and teachers at major universities. See where our graduates started their careers and published research.

• Publications
• Aakash Saxena PhD: 2020 Placement: Sykes Enterprises, Inc. Dissertation: A Method to Extract Context-Sensitive Semantics of a Concept Using Word-Embedding Space and Its Application  
• Jaebong Son  PhD: 2017 Placement - California State University Dissertation: What Have We Missed When Examining Twitter as a Communication Medium during Disasters  
• Jeffrey Sweeney  PhD: 2016 Placement: Erasmus University Dissertation: On Value Creation from Knowledge Management Systems  
• Jose Ramirez  PhD: 2015 Placement: United States Military Academy at West Point Dissertation: Essays on Military and Civilian Manpower Planning  
• Mark Zais  PhD: 2014 Placement: Office of the Secretary of Defense Dissertation: Simulation-Optimization, Markov Chain and Graph Coloring Approaches to Military Manpower Modeling and Deployment Sourcing  
• Subhamoy Ganguly PhD: 2013 Placement: Indian Institute of Management – Udaipur Dissertation: Essays in Scheduling: Applications in Health Care and Manufacturing  
• Jingjing Li  PhD: 2013 Placement: University of Virginia Dissertation: Addressing Information Proliferation: Applications of Information Extraction and Text Mining  
• Michele Samorani  PhD: 2012 Placement: University of Alberta, Canada Dissertation: Data Mining For Enhanced Operations Management Decision Making: Applications in Health Care  
• Tomasz Miaskiewicz  PhD: 2010 Initial Placement: The New University of Lisbon Current Placement: NOVA School of Business and Economics Dissertation: Bridging the Gap Between Consumers and Designers: The Role of Accurate and Effective Personas  
• Harald Reinertsen  PhD: 2010 Placement: Smith Stål Øst AS, Norway Dissertation: Optimization of the Industrial Cutting Stock Problems – Production Scheduling in a Dynamic Stochastic Environment  
• Zainab AlQenaei  PhD: 2009 Placement: Kuwait University Dissertation: An Investigation of the Relationship Between Consumer Mental Health Recovery Measures and Clinicians’ Reports Using Multivariate Analysis of the Singular Value Decomposition of a Textual Corpus  
• Marco Better  PhD: 2007 Placement: OptTek Systems, Inc. Dissertation: Data Mining Techniques for Prediction in Discrete Data Applications  
• Fang Liang  PhD: 2007 Placement: PROS Pricing Solutions Dissertation: The Hyperplan-Based Classification Techniques  
• Dirk Hovorka PhD: 2006 Placement: Bond University, Australia Dissertation: Information Systems Foundations: Four Research Essays  
• Rahul Patil  PhD: 2006 Placement: Indian Institute of Management Dissertation: Improved Techniques for Due Date Quotation in Realistic Production Environments  
• Emilio Collar  PhD: 2005 Placement: Western Connecticut State University Dissertation: An Investigation of Programming Code Textbase Readability Based on a Cognitive Readability Model  
• Younghwa Lee  PhD: 2005 Placement: University of Kansas Dissertation: Developing Theoretical Models of Website Usability  
• Mark W.S. Chun  PhD: 2003 Placement: Pepperdine University Dissertation: Embedded Knowledge, Embedded Information Systems: A Resource-Based Perspective on the System Integration Process During a Corporate Merger

Management Information Systems Quarterly   ( WITS 2016 Best Prototype Award ) Unlocking Knowledge Inheritance of Behavioral Research: A Design Framework and an Instantiation (Conditional acceptance) Jingjing Li—University of Virginia (PhD 2013) Kai Larsen –University of Colorado Boulder Ahmed Abbasi –University of Virginia

Information Systems Research Don’t Mention It? Analyzing User-generated Content Signals for Early Adverse Event Warnings   (2019) Ahmed Abbasi –University of Virginia Jingjing Li—University of Virginia (PhD 2013) Donald Adjeroh –West Virginia University Marie Abate—West Virginia University Wanhong Zheng –West Virginia University

MIS Quarterly      Information technology use as a learning mechanism: The impact of it  use on knowledge transfer effectiveness, absorptive capacity, and franchisee performance (2015) Kishen Iyengar - University of Colorado at Boulder Jeffrey R Sweeney - Maastricht University (PhD 2016) Ramiro Montealegre - University of Colorado at Boulder

MIS Quarterly      Can online wait be managed? The effect of filler interfaces and presentation modes on perceived waiting time online (2012) Younghwa Lee - University of Northern Iowa (PhD 2005) Andrew N.K. Chen - University of Kansas Virgina Ilie - California Luthern University

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Teaching Requirements

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Program at a Glance

This program is designed for students who seek training in advanced theoretical and applied issues in the field of information systems. The training prepares students for conducting leading-edge research in topics ranging from the design of optimized systems to the effective use of such systems in organizations. Students undergo rigorous training in research methodologies, as well as in the design of information systems. The research conducted is often interdisciplinary in nature and is characterized by strong analytical or econometric modeling of new and emerging issues in information technology management and creation. The program prepares students mainly for academic positions in research universities; some students may be placed in research positions in industry, government or consulting organizations.

The PhD in Information Systems program is characterized by a high ratio of research faculty to students, which fosters close working relationships. Students have the opportunity to be involved in ongoing faculty research projects under the mentorship of experienced professors. The close interaction with faculty enables students to quickly learn to identify and develop research ideas and create their own research agenda. Students also develop their teaching skills under faculty mentorship by teaching organized classes.

Successful candidates must possess a strong aptitude for abstract thinking and quantitative analysis to address relevant business problems. Students admitted into the PhD in Information Systems program devote the first few years to coursework and research projects, preparing for the qualifying examinations and developing their preliminary dissertation proposal. The next one to two years are devoted to dissertation research and writing. Students must complete at least 75 semester hours of approved graduate work before a degree may be conferred. Credit may be granted for courses taken elsewhere.

Program Contact

Srinivasan Raghunathan, PhD

Ashbel smith professor phd area coordinator, information systems.

[email protected] | (972) 883-4377 | JSOM 3.425

The Information Systems Doctoral program at the Naveen Jindal School of Management offers an outstanding opportunity for research in the Information Systems discipline. Our faculty’s research productivity usually ranks at the top in the world. More importantly, we work at the forefront of a variety of research topics and methodologies. Come join us to make this program even stronger!

Presently ranked #1 worldwide in research based on publications in three information systems journals, our Information Systems faculty are distinguished, pioneering researchers.

Faculty research pursuits range from quantitative modeling to empirical studies, mathematical programming, applied stochastic processes, statistics, econometrics, and economics.

With analytical depth and methodology, drawing from disciplines such as economics, operations research and econometrics, their research is both prevalent and employed in today’s rapidly changing technological world.

The UT Dallas Top 100 Worldwide Rankings of Business Schools based on Research Contributions in Information Systems Research, Journal on Computing, MIS Quarterly , 2017–2021.

Advanced and rigorous coursework, methodology and design, and significant placement on student research are the hallmarks of the Information Systems program.

The Information Systems program is characterized by a high ratio of research faculty to students which fosters close collaboration. Students have the opportunity to be involved in ongoing research projects under the mentorship of renown, distinguished faculty.

The program is designed for students to develop a strong aptitude for abstract thinking and quantitative analysis to address relevant business problems for their careers in academia or industry.

As shown in the table below, our Information Systems students have obtained top academic and industry appointments.

The close interaction with faculty enables students to quickly learn to identify and develop research ideas and create their own research agenda. Students also develop their teaching skills under faculty mentorship by teaching organized classes.

Below are examples of student publications in 24 leading business journals from 2017-2021.

Abhijeet Ghoshal , Atanu Lahiri, Debabrata Dey, 2021. “Support forums and software vendor’s pricing strategy.” Information Systems Research , vol. 32.

Srinivasan Raghunathan, Mehmet Ayvaci, YeongIn Kim , Huseyin Cavusoglu , 2021. “Designing payment contracts for healthcare services to induce information sharing: the adoption and the value of health information exchanges (hies).” MIS Quarterly , vol. 45.

Subodha Kumar , Min Chen , Min-Seok Pang, 2021. “Do you have room for us in your IT? An economic analysis of shared IT services and implications for IT industries.” MIS Quarterly , vol. 45.

Young Kwark , Liangfei Qiu, Gene Moo Lee, Paul A. Pavlou, 2021. “On the spillover effects of online product reviews on purchases: evidence from clickstream data.” Information Systems Research , vol. 32.

Sirong Luo, Dengpan Liu , Radha Mookerjee, 2021. “The effects of auction-based pricing mechanisms and social characteristics on microloan performance.” Productions and Operations Management , vol. 30.

Ganesh Janakiraman, Sameer Mehta , Vijay Mookerjee, Milind Dawande, 2021. “How to sell a data set? Pricing policies for data monetization.” Information Systems Research , vol. 32.

Jiahui Mo , Sumit Sarkar, Syam Menon, 2021. “Competing tasks and task quality: an empirical study of crowdsourcing contests.” MIS Quarterly , vol 45.

Murat M. Tunc , Huseyin Cavusoglu , Srinivasan Raghunathan, 2021. “Online product reviews: is a finer-grained rating scheme superior to a coarser one?” MIS Quarterly , vol. 45.

Mingwen Yang , Zhiqiang (Eric) Zheng, Vijay Mookerjee, 2021. “The race for online reputation: implications for platforms, firms, and consumers.” Information Systems Research , vol. 32.

Mingwen Yang , Varghese S. Jacob, Srinivasan Raghunathan, 2021. “Cloud service model’s role in provider and user security investment incentives.” Production and Operations Management , vol. 30.

Milind Dawande, Ganesh Janakiraman, Manmohan Aseri , Vijay S. Mookerjee, 2020. “Ad-blockers: a blessing or a curse?” Information Systems Research , vol. 31.

Chenzhang Bao , Kirk Kirksey, Indranil R. Bardhan, Bruce A. Myers, Harpreet Singh, 2020. “Patient–provider engagement and its impact on health outcomes: a longitudinal study of patient portal use.” MIS Quarterly , vol. 44.

Leila Hosseini , Vijay Mookerjee, Chelliah Sriskandarajah, Shaojie Tang, 2020. “A switch in time saves the dime: a model to reduce rental cost in cloud computing.” Information Systems Research , vol. 31.

Jianqing Chen, Srinivasan Raghunathan, Lusi Li , 2020. “Informative role of recommender systems in electronic marketplaces: a boon or a bane for competing sellers.” MIS Quarterly , vol. 44.

Sameer Mehta , Vijay Mookerjee, Milind Dawande, Ganesh Janakiraman, 2020. “Sustaining a good impression: mechanisms for selling partitioned impressions at ad exchanges.” Information Systems Research , vol. 31.

Zhiqiang (Eric) Zheng, Danish H. Saifee , Atanu Lahiri, Indranil R. Bardhan, 2020. “Are online reviews of physicians reliable indicators of clinical outcomes? a focus on chronic disease management.” Information Systems Research , vol. 31.

Ying Xie, Jayarajan Samuel , Zhiqiang (Eric) Zheng, 2020. “Value of local showrooms to online competitors.” MIS Quarterly , vol. 44.

Jyotishka Ray , Syam Menon, Vijay Mookerjee, 2020. “Bargaining over data: when does making the buyer more informed help?” Information Systems Research , vol. 31.

Zhiqiang (Eric) Zheng, Vijay Mookerjee, Mingwen Yang , 2019. “Prescribing response strategies to manage customer opinions: a stochastic differential equation approach.” Information Systems Research , vol. 30.

Zhengrui Jiang , Dipak C Jain, Xinxue Shawn Qu, 2019. “Optimal market entry timing for successive generations of technological innovations.” MIS Quarterly , vol. 43.

Xinxue Shawn Qu, Zhengrui Jiang, 2019. “A time-based dynamic synchronization policy for consolidated database systems.” MIS Quarterly , vol. 43.

Byungwan, Koh , Il-Horn Hann, Srinivasan Raghunathan, 2019. “Digitization of music: consumer adoption amidst piracy, unbundling, and rebundling.” MIS Quarterly , vol. 43.

Milind Dawande, Ganesh Janakiraman, Zhen Sun , Vijay Mookerjee, 2019. “Data-driven decisions for problems with an unspecified objective function.” Journal on Computing , vol. 31.

Yue Zhang , Jian-Yu Fisher Ke, Nan Hu , Ling Liu, 2019. “Risk pooling, supply chain hierarchy, and analysts’ forecasts.” Production and Operations Management , vol. 28.

Vijay Mookerjee, Milind Dawande, Ganesh Janakiraman, Manmohan Aseri , 2018. “Procurement policies for mobile-promotion platforms.” Management Science , vol. 64.

Srinivasan Raghunathan, Lusi Li , Jianqing Chen, 2018. “Recommender system rethink: implications for an electronic marketplace with competing manufacturers.” Information Systems Research , vol. 29.

Srinivasan Raghunathan, Young Kwark , Jianqing Chen, 2018. “User-generated content and competing firms product design.” Management Science , vol. 64.

Vijay Mookerjee, Yong Tan, Depngpan Liu , 2018. “When can ignorance be bliss: organizational structure and coordination in electronic retailing.” Information Systems Research , vol. 29.

Vijay Mookerjee, Dengpan Liu , 2018. “Advertising competition on the internet: operational and strategic considerations.” Production and Operations Management , vol. 27.

Mingzheng Wang, Yu Zhang, Zhengrui Jiang , Haifang Yang, 2018. “T-closeness slicing: a new privacy-preserving approach for transactional data publishing.” Journal on Computing , vol. 30.

Sarkar, Sumit, Menon, Syam, Mo, Jiahui , 2018. “Know when to run: recommendations in crowdsourcing contests.” MIS Quarterly , vol. 42.

Feng, Haiyang, Jiang, Zhengrui , Liu, Dengpan . “Quality, pricing, and release time: optimal market entry strategy for software-as-a-service vendors.” MIS Quarterly , 2018, vol. 42.

Bardhan, Indranil, Zheng, Zhiqiang, Ayabakan, Sezgin . “A data envelopment analysis approach to estimate it-enabled production capability.” MIS Quarterly , 2017, vol. 41.

Janakiraman, Ganesh, Sun, Zhen , Mookerjee, Vijay, Dawande, Milind. “Not just a fad: optimal sequencing in mobile in-app advertising.” Information Systems Research , 2017, vol. 28.

Ghoshal, Abhijeet , Lahiri, Atanu, Dey, Debabrata. “Drawing a line in the sand: Commitment problem in ending software support.” MIS Quarterly , 2017, vol. 41.

Mookerjee, Vijay, Cai, Yuanfeng, Jiang, Zhengrui . “How to deal with liars? Designing intelligent rule-based expert systems to increase accuracy or reduce cost.” Journal on Computing , 2017, vol. 29.

Nault, Barrie, Raghunathan, Srinivasan, Koh, Byungwan . “Is voluntary profiling welfare enhancing?” MIS Quarterly , 2017, vol. 41.

Raghunathan, Srinivasan, Cezar, Asunur , Cavusoglu, Huseyin. “Sourcing information security operations: the role of risk interdependency and competitive externality in outsourcing decisions.” Production and Operations Management , 2017, vol. 26.

Raghunathan, Srinivasan, Kwark, Young , Chen, Jianqing. “Platform or wholesale? A strategic tool for online retailers to benefit from third-party information.” MIS Quarterly , 2017, vol. 41.

Ray, Jyotishka , Samuel, Jayarajan , Menon, Syam, Mookerjee, Vijay. “The design of feature-limited demonstration software: choosing the right features to include.” Production and Operations Management , 2017, vol. 26.

Zhang, Jie, Hu, Nan , Pavlou, Paul. “On self-selection biases in online product reviews.” MIS Quarterly , 2017, vol. 41.

Zheng, Zhiqiang, Ayabakan, Sezgin , Kirksey, Kirk, Bardhan, Indranil. “The impact of health information sharing on duplicate testing.” MIS Quarterly , 2017, vol. 41.

Chen, Hongyu , Zheng, Zhiqiang, Ceran, Yasin. “De-biasing the reporting bias in social media analytics.” Production and Operations Management , 2016, vol. 25.

Hann, Il-Horn, Koh, Byungwan , Niculescu, Marius. “The double-edged sword of backward compatibility: the adoption of multigenerational platforms in the presence of intergenerational services.” Information Systems Research , 2016, vol. 27.

Janakiraman, Ganesh, Sun, Zhen , Mookerjee, Vijay, Dawande, Milind. “The making of a good impression: information hiding in ad exchanges.” MIS Quarterly, 2016, vol. 40.

Lee, Chul Ho , Geng, Xianjun, Raghunathan, Srinivasan. “Mandatory standards and organizational information security.” Information Systems Research , 2016, vol. 27.

Mookerjee, Vijay, Ceran, Yasin , Singh, Harpreet. “Knowing what your customer wants: improving inventory allocation decisions in online movie rental systems.” Production and Operations Management , 2016, vol. 25.

Xia, Hao , Dawande, Milind, Mookerjee, Vijay. “Optimal coordination in distributed software development.” Production and Operations Management , 2016, vol. 25.

Admission Procedures

Applicants should have at least a bachelor’s degree. Admission is based on grade point average, graduate examination test score (GMAT* or GRE), letters of reference (at least three, with two from academic references), business and professional experience (if applicable), a written statement of personal objectives and compatibility with faculty research activities. Since the School of Management starts making first-round admission decisions on December 9, it is best to complete the entire application process no later than December 8. While applications will be accepted after that date, applying after December 8 may significantly lower your chance of acceptance. Applications for admission can be made using the UT Dallas Graduate Application website .

* UT Dallas Naveen Jindal School of Management prefers the GMAT admission test, however, we gladly accept the GRE test as well.

Degree Requirements

Calculus, matrix algebra, computer programming and statistics are prerequisites for the doctoral program – every admitted student is responsible for ensuring he/she has satisfied these prerequisite requirements before joining the program.

Doctoral students in Management Science benefit from an exposure to multiple functional areas in management. To ensure this benefit, students who enter the program without an MBA (or equivalent degree) are required to complete a combined minimum of four courses (at the master’s or doctoral level) in at least three functional areas. This cross-functional exposure is particularly useful for students engaging in cross-functional research, in positioning their research for wider appeal, and for effectively teaching business school students with diverse specializations.

The Management Science PhD core curriculum consists of a minimum of 9 courses.

Please visit the Management Science Degree Plan page for core and secondary core course requirements.

Nine hours in any approved field

Students are required to take a sequence of specific courses. Students should consult with faculty members in their respective areas to decide on the sequence of courses.

Twelve hours of special topics and seminars in the information systems area.

Students are required to write original research papers in both their first and second summers. The second year paper is presented in a seminar attended by faculty and other students, and must be judged to be passing by the faculty before the student can advance to candidacy.

PhD in Information Systems students take a written preliminary exam at the end of their first year in the program over a set of core methodology courses ( MECO 6315 Statistics, MECO 6345 Advanced Managerial Economics, MECO 6350 Game Theory, OPRE 7353 Optimization). At the end of their fifth semester in the program, students take a qualifying exam (consisting of two parts: a written exam that tests their knowledge of information systems theory and applications, and a completed research paper).

PhD students must successfully complete the preliminary and qualifying examinations, respectively, to enter PhD candidacy. The area faculty will determine whether a student has successfully completed the exam requirements based on the student’s performance. Criteria to evaluate students may include results from the in-class written portion of the exams, quality of research papers and/or presentations, performance in special courses (e.g. seminar courses), satisfactory GPA as determined by area faculty, and other forms of assessment as required by the student’s area. An unsatisfactory performance in any one criteria for either the preliminary examination or the qualifying examination may result in dismissal from the program.

Once the student has passed qualifying exam and paper requirements, work on the dissertation can commence. The dissertation is written under the direction of the dissertation committee. Twelve to 24 semester hours may be granted for the dissertation toward the minimum 75-hour requirement for the degree. At a time mutually agreeable to the candidate and the dissertation committee, the candidate must orally defend the dissertation to the committee.

The Dissertation Proposal must be successfully defended at least one semester prior to the term of graduation. The requirements for the proposal defense should be discussed with the dissertation committee prior to scheduling the defense. Dissertation Proposal Defenses will be open to all faculty and PhD students of the Jindal School of Management.

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Before you apply, get familiar with the admission requirements and application process for Jindal School PhD programs at UT Dallas.

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Information Science: PhD

About the Program

The doctoral program.

The doctoral program in Information Science is a research-oriented program in which the student chooses specific fields of specialization, prepares sufficiently in the literature and the research of those fields to pass a qualifying examination, and completes original research culminating in the written dissertation. The degree of Doctor of Philosophy is conferred in recognition of a candidate's grasp of a broad field of learning and distinguished accomplishment in that field through the contribution of an original piece of research revealing high critical ability and powers of imagination and synthesis.

The I School also offers a master's in Information Management and Systems (MIMS), a master's in  Information and Data Science  (MIDS), and a master's in  Information and Cybersecurity (MICS).

Visit School Website

Admission to the PhD Program

We welcome students from a diverse set of backgrounds; some will be technically educated, some educated in the humanities and social sciences.

The I School typically accepts 3-7 PhD students each year from more than 100 applications. Applications are reviewed by a committee of faculty.

Applicants are evaluated holistically on a number of factors. A strong academic record is important, but not sufficient. A critical factor is the ability to demonstrate a research record and agenda that fit well with specific I School faculty. In a small, interdisciplinary program, it is important that applicants clearly indicate in their Statement of Purpose which faculty member(s) they are interested in researching with, and why.

To be eligible to apply to the PhD in Information Management and Systems program, applicants must meet the following requirements:

A bachelor's degree or its recognized equivalent from an accredited institution.

Superior scholastic record, normally well above a 3.0 GPA.

Indication of appropriate research goals, described in the Statement of Purpose.

For applicants whose academic work has been in a language other than English, the Test of English as a Foreign Language (TOEFL) or International English Language Testing System (IELTS).

Not required: GRE/GMAT. Starting Fall 2021, we no longer require the GRE or GMAT. We recommend you put your time and effort towards the required application materials.

Further  information about I School Ph.D. Admissions  can be found on the I School website. 

Applying for Graduate Admission

Thank you for considering UC Berkeley for graduate study! UC Berkeley offers more than 120 graduate programs representing the breadth and depth of interdisciplinary scholarship. The Graduate Division hosts a complete list of graduate academic programs, departments, degrees offered, and application deadlines can be found on the Graduate Division website.

Prospective students must submit an online application to be considered for admission, in addition to any supplemental materials specific to the program for which they are applying. The online application and steps to take to apply can be found on the Graduate Division website .

Admission Requirements

The minimum graduate admission requirements are:

A bachelor’s degree or recognized equivalent from an accredited institution;

A satisfactory scholastic average, usually a minimum grade-point average (GPA) of 3.0 (B) on a 4.0 scale; and

Enough undergraduate training to do graduate work in your chosen field.

For a list of requirements to complete your graduate application, please see the Graduate Division’s Admissions Requirements page . It is also important to check with the program or department of interest, as they may have additional requirements specific to their program of study and degree. Department contact information can be found here .

Where to apply?

Visit the Berkeley Graduate Division application page .

Doctoral Degree Requirements

Program design.

The School of Information is an interdisciplinary school examining the design, organization, and management of information and information systems. The School of Information draws on the expertise not only of its own faculty but of the full Berkeley campus. We encourage students to take full advantage of being at this world-class University and not feel bound by disciplinary boundaries.

The PhD degree program at the School of Information is a research program. Each student is expected to work with his or her adviser to ensure that the program of study includes:

• A thorough understanding of research methods and research design.
• The ability to review current research critically.
• The ability to understand emerging trends from an interdisciplinary perspective.

Expected PhD Timeline:

• Semester 1:  Identify a faculty adviser
• Semesters 1–4:  Complete breadth courses; complete major and minor requirements
• Semester 4:  Complete the preliminary research paper
• Semester 5:  Complete preliminary exam
• Semester 6–8:  Complete qualifying exam; advance to candidacy
• Four semesters after qualifying exam:  Complete dissertation and give presentation

Please refer to  the School of Information website  for more information.

Breadth Courses

Major/Minor Areas

Related Courses

Info 201 research design and applications for data and analysis 3 units.

Terms offered: Fall 2024, Spring 2024, Fall 2023 Introduces the data sciences landscape, with a particular focus on learning data science techniques to uncover and answer the questions students will encounter in industry. Lectures, readings, discussions, and assignments will teach how to apply disciplined, creative methods to ask better questions, gather data, interpret results, and convey findings to various audiences. The emphasis throughout is on making practical contributions to real decisions that organizations will and should make. Course must be taken for a letter grade to fulfill degree requirements. Research Design and Applications for Data and Analysis: Read More [+]

Hours & Format

Fall and/or spring: 15 weeks - 1.5 hours of lecture per week

Additional Format: One and one-half hours of lecture per week.

Additional Details

Subject/Course Level: Information/Graduate

Grading: Letter grade.

Research Design and Applications for Data and Analysis: Read Less [-]

INFO 202 Information Organization and Retrieval 3 Units

Terms offered: Fall 2024, Fall 2023, Fall 2022 This course introduces the intellectual foundations of information organization and retrieval: conceptual modeling, semantic representation, vocabulary and metadata design, classification, and standardization, as well as information retrieval practices, technology, and applications, including computational processes for analyzing information in both textual and non-textual formats. Information Organization and Retrieval: Read More [+]

Rules & Requirements

Prerequisites: Students should have a working knowledge of the Python programming language

Fall and/or spring: 15 weeks - 3 hours of lecture per week

Additional Format: Three hours of lecture per week.

Information Organization and Retrieval: Read Less [-]

INFO 203 Social Issues of Information 3 Units

Terms offered: Spring 2024, Spring 2023, Spring 2022 This course is designed to be an introduction to the topics and issues associated with information and information technology and its role in society. Throughout the semester we will consider both the consequence and impact of technologies on social groups and on social interaction and how society defines and shapes the technologies that are produced. Students will be exposed to a broad range of applied and practical problems, theoretical issues, as well as methods used in social scientific analysis. The four sections of the course are: 1) theories of technology in society, 2) information technology in workplaces 3) automation vs. humans, and 4) networked sociability. Social Issues of Information: Read More [+]

Social Issues of Information: Read Less [-]

INFO 205 Information Law and Policy 3 Units

Terms offered: Spring 2024, Spring 2023, Spring 2022 This course uses examples from various commercial domains—retail, health, credit, entertainment, social media, and biosensing/quantified self—to explore legal and ethical issues including freedom of expression, privacy, research ethics, consumer protection, information and cybersecurity, and copyright. The class emphasizes how existing legal and policy frameworks constrain, inform, and enable the architecture, interfaces, data practices, and consumer facing policies and documentation of such offerings; and, fosters reflection on the ethical impact of information and communication technologies and the role of information professionals in legal and ethical work. Information Law and Policy: Read More [+]

Prerequisites: Consent of instructor required for nonmajors

Instructor: Mulligan

Information Law and Policy: Read Less [-]

INFO 206A Introduction to Programming and Computation 2 Units

Terms offered: Fall 2024, Fall 2023, Fall 2022 This course introduces the basics of computer programming that are essential for those interested in computer science, data science, and information management. Students will write their own interactive programs (in Python) to analyze data, process text, draw graphics, manipulate images, and simulate physical systems. Problem decomposition, program efficiency, and good programming style are emphasized throughout the course. Introduction to Programming and Computation: Read More [+]

Fall and/or spring: 7.5 weeks - 4 hours of lecture per week

Additional Format: Four hours of lecture per week for seven and one-half weeks.

Instructor: Farid

Introduction to Programming and Computation: Read Less [-]

INFO 206B Introduction to Data Structures and Analytics 2 Units

Terms offered: Fall 2024, Fall 2023, Fall 2022 The ability to represent, manipulate, and analyze structured data sets is foundational to the modern practice of data science. This course introduces students to the fundamentals of data structures and data analysis (in Python). Best practices for writing code are emphasized throughout the course. This course forms the second half of a sequence that begins with INFO 106. It may also be taken as a stand-alone course by any student that has sufficient Python experience. Introduction to Data Structures and Analytics: Read More [+]

Prerequisites: INFO 206A or equivalent, or permission of instructor

Credit Restrictions: Course must be completed for a letter grade to fulfill degree requirements.

Formerly known as: Information 206

Introduction to Data Structures and Analytics: Read Less [-]

INFO 213 Introduction to User Experience Design 4 Units

Terms offered: Fall 2024, Fall 2023, Fall 2022 This course will provide an introduction to the field of Human-Computer Interaction (HCI). Students will learn to apply design thinking to User Experience (UX) design, prototyping, & evaluation. The course will also cover special topic areas within HCI. Introduction to User Experience Design: Read More [+]

Introduction to User Experience Design: Read Less [-]

INFO 214 User Experience Research 3 Units

Terms offered: Spring 2024, Spring 2023, Spring 2022 This course addresses concepts and methods of user experience research, from understanding and identifying needs, to evaluating concepts and designs, to assessing the usability of products and solutions. We emphasize methods of collecting and interpreting qualitative data about user activities, working both individually and in teams, and translating them into design decisions. Students gain hands-on practice with observation, interview, survey , focus groups, and expert review. Team activities and group work are required during class and for most assignments. Additional topics include research in enterprise, consulting, and startup organizations, lean/agile techniques, mobile research approaches, and strategies for communicating findings. User Experience Research: Read More [+]

Additional Format: Three hours of Lecture per week for 15 weeks.

User Experience Research: Read Less [-]

INFO 215 Product Design Studio 3 Units

Terms offered: Fall 2024, Fall 2023 This course will give participants hands-on digital product design experience oriented around current industry practice. The course will be project-based with an emphasis on iteration, practice, and critique. During the course, participants will work on a series of design projects through a full design process, including developing appropriate design deliverables, gathering feedback, and iterating on designs. Product Design Studio: Read More [+]

Objectives & Outcomes

Course Objectives: The course objective is to provide students interested in web and mobile Product Design with skills, practice, and experience that will prepare them for careers in product design and design-related roles.

Prerequisites: DES INV 15 or COMPSCI 160 or INFO 213 AND INFO 214; or permission of the instructor. Students can take INFO 214 and INFO 215 concurrently, but students may not drop INFO 214 and remain in INFO 215

Formerly known as: Information Systems and Management 215

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INFO 217A Human-Computer Interaction (HCI) Research 3 Units

Terms offered: Spring 2024, Fall 2021, Fall 2020 This course is a graduate-level introduction to HCI research. Students will learn to conduct original HCI research by reading and discussing research papers while collaborating on a semester-long research project. Each week the class will focus on a theme of HCI research and review foundational and cutting-edge research relevant to that theme. The class will focus on the following areas of HCI research: ubiquitous computing , social computing, critical theory, and human-AI interaction. In addition to these research topics the class will introduce common qualitative and quantitative methodologies in HCI research. Human-Computer Interaction (HCI) Research: Read More [+]

Instructor: Salehi

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INFO 218 Concepts of Information 3 Units

Terms offered: Spring 2024, Spring 2022, Spring 2020 As it's generally used, "information" is a collection of notions, rather than a single coherent concept. In this course, we'll examine conceptions of information based in information theory, philosophy, social science, economics, and history. Issues include: How compatible are these conceptions; can we talk about "information" in the abstract? What work do these various notions play in discussions of literacy, intellectual property, advertising, and the political process? And where does this leave "information studies" and "the information society"? Concepts of Information: Read More [+]

Prerequisites: Graduate standing

Instructors: Duguid, Nunberg

Concepts of Information: Read Less [-]

INFO 225 Leadership and Management 3 Units

Terms offered: Fall 2024, Fall 2023, Fall 2021 This course focuses on the practice of leadership, collaboration, and people management in contemporary, distributed, information and technology-rich organizations. Not just for potential people managers, this course is derived from the premise that a foundation in leadership, management, and collaboration is essential for individuals in all roles, at any stage of their career. To build this foundation we will take a hybrid approach, engaging literature from disciplines such as social psychology, management, and organizational behavior, as well as leveraging case studies and practical exercises. The course will place a special emphasis on understanding and reacting to social dynamics in workplace hierarchies and teams. Leadership and Management: Read More [+]

Leadership and Management: Read Less [-]

INFO 231 Decisions and Algorithms 3 Units

Terms offered: Fall 2024, Spring 2013, Spring 2011 This class is for graduate students interested in getting an advanced understanding of judgments and decisions made with predictive algorithms. The course will survey the vast literature on the psychology of how people arrive at judgments and make decisions with the help of statistical information, focused mostly on experimental lab evidence from cognitive and social psychology. Then study the burgeoning evidence on how people use statistical algorithms in practice, exploring field evidence from a range of settings from criminal justice and healthcare to housing and labor markets. Special attention is paid to psychological principles that impact the effectiveness and fairness of algorithms deployed at scale. Decisions and Algorithms: Read More [+]

Course Objectives: Help students understand systematic human errors and explore potential algorithmic solutions.

Decisions and Algorithms: Read Less [-]

INFO 233 Social Psychology and Information Technology 3 Units

Terms offered: Spring 2024, Spring 2023, Spring 2022 Discusses application of social psychological theory and research to information technologies and systems; we focus on sociological social psychology, which largely focuses on group processes, networks, and interpersonal relationships. Information technologies considered include software systems used on the internet such as social networks, email, and social games, as well as specific hardware technologies such as mobile devices, computers , wearables, and virtual/augmented reality devices. We examine human communication practices, through the lens of different social psychology theories, including: symbolic interaction, identity theories, social exchange theory, status construction theory, and social networks and social structure theory. Social Psychology and Information Technology: Read More [+]

Instructor: Cheshire

Social Psychology and Information Technology: Read Less [-]

INFO 234 Information Technology Economics, Strategy, and Policy 3 Units

Terms offered: Spring 2024, Spring 2022, Spring 2021 This course applies economic tools and principles, including game theory, industrial organization, information economics, and behavioral economics, to analyze business strategies and public policy issues surrounding information technologies and IT industries. Topics include: economics of information goods, services, and platforms; economics of information and asymmetric information; economics of artificial intelligence, cybersecurity, data privacy, and peer production; strategic pricing; strategic complements and substitutes; competition and antitrust; Internet industry structure and regulation; network cascades, network formation, and network structure. Information Technology Economics, Strategy, and Policy: Read More [+]

Course Objectives: INFO234 is a graduate level course in the school's topical area of Information Economics and Policy, and can be taken by the masters and doctoral students to satisfy their respective degree requirements.

Student Learning Outcomes: Students will learn to identify, describe, and analyze business strategies and public policy issues of particular relevance to the information industry. Students will learn and apply economic tools and principles to analyze phenomena such as platform competition, social epidemics, and peer production, and current policy issues such as network neutrality and information privacy. Through integrated assignments and project work, the students will apply the theoretical concepts and analytic tools learned in lectures and readings to develop and evaluate a business model, product, or service of their choosing, e.g., a start-up idea they are pursuing.

Instructor: Chuang

Information Technology Economics, Strategy, and Policy: Read Less [-]

INFO 239 Technology and Delegation 3 Units

Terms offered: Fall 2021, Fall 2019, Fall 2018 The introduction of technology increasingly delegates responsibility to technical actors, often reducing traditional forms of transparency and challenging traditional methods for accountability. This course explores the interaction between technical design and values including: privacy, accessibility, fairness, and freedom of expression. We will draw on literature from design, science and technology studies, computer science, law, and ethics, as well as primary sources in policy, standards and source code. We will investigate approaches to identifying the value implications of technical designs and use methods and tools for intentionally building in values at the outset. Technology and Delegation: Read More [+]

Technology and Delegation: Read Less [-]

INFO 241 Experiments and Causal Inference 3 Units

Terms offered: Fall 2024, Spring 2024, Fall 2022 This course introduces students to experimentation in data science. Particular attention is paid to the formation of causal questions, and the design and analysis of experiments to provide answers to these questions. This topic has increased considerably in importance since 1995, as researchers have learned to think creatively about how to generate data in more scientific ways, and developments in information technology has facilitated the development of better data gathering. Experiments and Causal Inference: Read More [+]

Experiments and Causal Inference: Read Less [-]

INFO 247 Information Visualization and Presentation 4 Units

Terms offered: Spring 2023, Spring 2022, Spring 2021 The design and presentation of digital information. Use of graphics, animation, sound, visualization software, and hypermedia in presenting information to the user. Methods of presenting complex information to enhance comprehension and analysis. Incorporation of visualization techniques into human-computer interfaces. Course must be completed for a letter grade to fulfill degree requirements. Information Visualization and Presentation: Read More [+]

Prerequisites: INFO 206B or knowledge of programming and data structures with consent of instructor

Fall and/or spring: 15 weeks - 3 hours of lecture and 1 hour of laboratory per week

Additional Format: Three hours of lecture and one hour of laboratory per week.

Instructor: Hearst

Information Visualization and Presentation: Read Less [-]

INFO 251 Applied Machine Learning 4 Units

Terms offered: Spring 2024, Spring 2023, Spring 2022 Provides a theoretical and practical introduction to modern techniques in applied machine learning. Covers key concepts in supervised and unsupervised machine learning, including the design of machine learning experiments, algorithms for prediction and inference, optimization, and evaluation. Students will learn functional, procedural, and statistical programming techniques for working with real-world data. Applied Machine Learning: Read More [+]

Student Learning Outcomes: • Effectively design, execute, and critique experimental and non-experimental methods from statistics, machine learning, and econometrics. • Implement basic algorithms on structured and unstructured data, and evaluate the performance of these algorithms on a variety of real-world datasets. • Understand the difference between causal and non-causal relationships, and which situations and methods are appropriate for both forms of analysis. • Understand the principles, advantages, and disadvantages of different algorithms for supervised and unsupervised machine learning.

Prerequisites: INFO 206B , or equivalent course in Python programming; INFO 271B , or equivalent graduate-level course in statistics or econometrics; or permission of instructor

Fall and/or spring: 15 weeks - 3 hours of lecture and 1 hour of discussion per week

Additional Format: Three hours of lecture and one hour of discussion per week.

Instructor: Blumenstock

Applied Machine Learning: Read Less [-]

INFO 253A Front-End Web Architecture 3 Units

Terms offered: Fall 2024, Fall 2023, Fall 2022 This course is a survey of technologies that power the user interfaces of web applications on a variety of devices today, including desktop, mobile, and tablet devices. This course will delve into some of the core Front-End languages and frameworks (HTML/CSS/JS/React/Redux), as well as the underlying technologies enable web applications (HTTP, URI, JSON). The goal of this course is to provide an overview of the technical issues surrounding user interfaces powered by the web today, and to provide a solid and comprehensive perspective of the Web's constantly evolving landscape. Front-End Web Architecture: Read More [+]

Prerequisites: Introductory programming

Fall and/or spring: 15 weeks - 2 hours of lecture and 1 hour of laboratory per week

Additional Format: Two hours of lecture and one hour of laboratory per week.

Formerly known as: Information 253

Front-End Web Architecture: Read Less [-]

INFO 253B Back-End Web Architecture 3 Units

Terms offered: Spring 2024, Spring 2023, Spring 2022 This course is a survey of web technologies that are used to build back-end systems that enable rich web applications. Utilizing technologies such as Python, Flask, Docker, RDBMS/NoSQL databases, and Spark, this class aims to cover the foundational concepts that drive the web today. This class focuses on building APIs using micro-services that power everything from content management systems to data engineering pipelines that provide insights by processing large amounts of data. The goal of this course is to provide an overview of the technical issues surrounding back-end systems today, and to provide a solid and comprehensive perspective of the web's constantly evolving landscape. Back-End Web Architecture: Read More [+]

Back-End Web Architecture: Read Less [-]

INFO 255 Privacy Engineering 3 Units

Terms offered: Spring 2024, Spring 2023 The course overviews a broad number of paradigms of privacy from a technical point of view. The course is designed to assist system engineers and information systems professionals in getting familiar with the subject of privacy engineering and train them in implementing those mechanisms. In addition, the course is designed to coach those professionals to critically think about the strengths and weaknesses of the different privacy paradigms. These skills are important for cybersecurity professionals and enable them to effectively incorporate privacy-awareness in the design phase of their products. Privacy Engineering: Read More [+]

Course Objectives: Critique the strengths and weaknesses of the different privacy paradigms Describe the different technical paradigms of privacy that are applicable for systems engineering Implement such privacy paradigms, and embed them in information systems during the design process and the implementation phase Stay updated about the state of the art in the field of privacy engineering

Credit Restrictions: Students will receive no credit for INFO 255 after completing INFO 255 . A deficient grade in INFO 255 may be removed by taking INFO 255 .

Privacy Engineering: Read Less [-]

INFO 256 Applied Natural Language Processing 3 Units

Terms offered: Fall 2024, Fall 2023, Fall 2021 This course examines the use of natural language processing as a set of methods for exploring and reasoning about text as data, focusing especially on the applied side of NLP — using existing NLP methods and libraries in Python in new and creative ways. Topics include part-of-speech tagging, shallow parsing, text classification, information extraction, incorporation of lexicons and ontologies into text analysis, and question answering. Students will apply and extend existing software tools to text-processing problems. Applied Natural Language Processing: Read More [+]

Prerequisites: INFO 206A and INFO 206B or proficient programming in Python (programs of at least 200 lines of code). Proficient with basic statistics and probabilities

Instructor: Bamman

Applied Natural Language Processing: Read Less [-]

INFO 258 Data Engineering 4 Units

Terms offered: Spring 2024, Fall 2022 This course will cover the principles and practices of managing data at scale, with a focus on use cases in data analysis and machine learning. We will cover the entire life cycle of data management and science, ranging from data preparation to exploration, visualization and analysis, to machine learning and collaboration, with a focus on ensuring reliable, scalable operationalization. ensuring reliable, scalable operationalization. Data Engineering: Read More [+]

Prerequisites: INFO 206B or equivalent college-level course in computer science in Python with a C- or better AND COMPSCI C100/ DATA C100 / STAT C100 or COMPSCI 189 or INFO 251 or DATA 144 or equivalent college-level course in data science with a C- or better

Instructors: Hellerstein, Parameswaran, Jain

Data Engineering: Read Less [-]

INFO 259 Natural Language Processing 4 Units

Terms offered: Spring 2024, Spring 2023, Spring 2022 This course introduces students to natural language processing and exposes them to the variety of methods available for reasoning about text in computational systems. NLP is deeply interdisciplinary, drawing on both linguistics and computer science, and helps drive much contemporary work in text analysis (as used in computational social science, the digital humanities, and computational journalism). We will focus on major algorithms used in NLP for various applications (part-of-speech tagging, parsing, coreference resolution, machine translation) and on the linguistic phenomena those algorithms attempt to model. Students will implement algorithms and create linguistically annotated data on which those algorithms depend. Natural Language Processing: Read More [+]

Prerequisites: Familiarity with data structures, algorithms, linear algebra, and probability

Natural Language Processing: Read Less [-]

INFO C262 Theory and Practice of Tangible User Interfaces 4 Units

Terms offered: Fall 2024, Fall 2023, Fall 2022 This course explores the theory and practice of Tangible User Interfaces, a new approach to Human Computer Interaction that focuses on the physical interaction with computational media. The topics covered in the course include theoretical framework, design examples, enabling technologies, and evaluation of Tangible User Interfaces. Students will design and develop experimental Tangible User Interfaces using physical computing prototyping tools and write a final project report. Theory and Practice of Tangible User Interfaces: Read More [+]

Instructor: Ryokai

Also listed as: NWMEDIA C262

Theory and Practice of Tangible User Interfaces: Read Less [-]

INFO C265 Interface Aesthetics 3 Units

Terms offered: Spring 2024, Spring 2023, Spring 2022 This course will cover new interface metaphors beyond desktops (e.g., for mobile devices, computationally enhanced environments, tangible user interfaces) but will also cover visual design basics (e.g., color, layout, typography, iconography) so that we have systematic and critical understanding of aesthetically engaging interfaces. Students will get a hands-on learning experience on these topics through course projects, design critiques , and discussions, in addition to lectures and readings. Interface Aesthetics: Read More [+]

Also listed as: NWMEDIA C265

Interface Aesthetics: Read Less [-]

INFO 271B Quantitative Research Methods for Information Systems and Management 3 Units

Terms offered: Fall 2024, Fall 2023, Fall 2022 Introduction to many different types of quantitative research methods, with an emphasis on linking quantitative statistical techniques to real-world research methods. Introductory and intermediate topics include: defining research problems, theory testing, casual inference, probability, and univariate statistics. Research design and methodology topics include: primary/secondary survey data analysis, experimental designs, and coding qualitative data for quantitative analysis. Quantitative Research Methods for Information Systems and Management: Read More [+]

Prerequisites: Introductory statistics recommended

Quantitative Research Methods for Information Systems and Management: Read Less [-]

INFO 272 Qualitative Research Methods for Information Systems and Management 3 Units

Terms offered: Fall 2024, Fall 2023, Fall 2022 Theory and practice of naturalistic inquiry. Grounded theory. Ethnographic methods including interviews, focus groups, naturalistic observation. Case studies. Analysis of qualitative data. Issues of validity and generalizability in qualitative research. Qualitative Research Methods for Information Systems and Management: Read More [+]

Instructor: Burrell

Qualitative Research Methods for Information Systems and Management: Read Less [-]

INFO 283 Information and Communications Technology for Development 3 Units

Terms offered: Spring 2024, Spring 2023, Spring 2022 This seminar reviews current literature and debates regarding Information and Communication Technologies and Development (ICTD). This is an interdisciplinary and practice-oriented field that draws on insights from economics, sociology, engineering, computer science, management, public health, etc. Information and Communications Technology for Development: Read More [+]

Fall and/or spring: 15 weeks - 3 hours of seminar per week

Additional Format: Three hours of seminar per week.

Instructor: Saxenian

Formerly known as: Information C283

Information and Communications Technology for Development: Read Less [-]

INFO 288 Big Data and Development 3 Units

Terms offered: Spring 2024, Spring 2021, Spring 2019 As new sources of digital data proliferate in developing economies, there is the exciting possibility that such data could be used to benefit the world’s poor. Through a careful reading of recent research and through hands-on analysis of large-scale datasets, this course introduces students to the opportunities and challenges for data-intensive approaches to international development. Students should be prepared to dissect, discuss, and replicate academic publications from several fields including development economics, machine learning, information science, and computational social science. Students will also conduct original statistical and computational analysis of real-world data. Big Data and Development: Read More [+]

Prerequisites: Students are expected to have prior graduate training in machine learning, econometrics, or a related field

Big Data and Development: Read Less [-]

INFO 289 Public Interest Cybersecurity: The Citizen Clinic Practicum 3 Units

Terms offered: Fall 2024, Spring 2024, Fall 2023 This course provides students with real-world experience assisting politically vulnerable organizations and persons around the world to develop and implement sound cybersecurity practices. In the classroom, students study basic theories and practices of digital security, intricacies of protecting largely under-resourced organizations, and tools needed to manage risk in complex political, sociological, legal, and ethical contexts. In the clinic , students work in teams supervised by Clinic staff to provide direct cybersecurity assistance to civil society organizations. We emphasize pragmatic, workable solutions that take into account the unique needs of each partner organization. Public Interest Cybersecurity: The Citizen Clinic Practicum: Read More [+]

Repeat rules: Course may be repeated for credit with instructor consent.

Public Interest Cybersecurity: The Citizen Clinic Practicum: Read Less [-]

INFO 290 Special Topics in Information 1 - 4 Units

Terms offered: Fall 2024, Spring 2024, Fall 2023 Specific topics, hours, and credit may vary from section to section, year to year. Special Topics in Information: Read More [+]

Repeat rules: Course may be repeated for credit when topic changes. Students may enroll in multiple sections of this course within the same semester.

Fall and/or spring: 8 weeks - 2-8 hours of lecture per week 15 weeks - 1-4 hours of lecture per week

Summer: 10 weeks - 1.5-6 hours of lecture per week

Additional Format: One to four hours of lecture per week. One and one-half to six hours of lecture per week for 10 weeks. Two to eight hours of lecture per week for 8 weeks.

Special Topics in Information: Read Less [-]

INFO 290M Special Topics in Management 1 - 4 Units

Terms offered: Fall 2024, Spring 2024, Fall 2023 Specific topics, hours, and credit may vary from section to section and year to year. Special Topics in Management: Read More [+]

Additional Format: One to four hours of lecture per week. Two to eight hours of lecture per week for 8 weeks.

Special Topics in Management: Read Less [-]

INFO 290S Special Topics in Social Science and Policy 2 - 4 Units

Terms offered: Fall 2024, Fall 2023, Spring 2023 Specific topics, hours, and credit may vary from section to section and year to year. Special Topics in Social Science and Policy: Read More [+]

Fall and/or spring: 8 weeks - 4-8 hours of lecture per week 15 weeks - 2-4 hours of lecture per week

Additional Format: Two to four hours of lecture per week. Four to eight hours of lecture per week for 8 weeks.

Special Topics in Social Science and Policy: Read Less [-]

INFO 290T Special Topics in Technology 2 - 4 Units

Terms offered: Spring 2024, Fall 2023, Spring 2023 Specific topics, hours, and credit may vary from section to section and year to year. Special Topics in Technology: Read More [+]

Special Topics in Technology: Read Less [-]

INFO 291 Special Topics in Information 1 - 4 Units

Terms offered: Prior to 2007 Specific topics, hours, and credit may vary from section to section, year to year. Special Topics in Information: Read More [+]

Repeat rules: Course may be repeated for credit when topic changes.

Fall and/or spring: 15 weeks - 1-4 hours of lecture per week

Additional Format: One to four hours of lecture per week.

Grading: Offered for satisfactory/unsatisfactory grade only.

Instructor: Hoofnagle

INFO 293 Information Management Practicum 0.5 Units

Terms offered: Fall 2016, Summer 2016 10 Week Session, Spring 2016 This course is designed to help School of Information graduate students maximize their internship, practicum, or independent research experiences. Information Management Practicum: Read More [+]

Course Objectives: Experience the practical application of your academic knowledge to real-world professional contexts; Gain insight into an organization and how one might make a valuable contribution; Reflect on the information the experience has provided, to see if it fits within one’s personal value set and work/life manifestos. Try out various professional activities to see when you are in ‘flow’;

Student Learning Outcomes: Assess the organizational culture of a company, governmental body, or non-governmental organization Connect academic knowledge about information management to real-world professional contexts Evaluate the effectiveness of a variety of information science techniques when deployed in organizational situations Integrate the student's own individual professional goals with the organization's needs relevant to the internship or practicum Reflect critically on the internship or practicum experience

Prerequisites: Consent of a Head Graduate Adviser for the School of Information

Repeat rules: Course may be repeated for credit without restriction.

Fall and/or spring: 15 weeks - 1 hour of internship per week

Summer: 10 weeks - 1.5 hours of internship per week

Additional Format: One hour of internship per week. One and one-half hours of internship per week for 10 weeks.

Information Management Practicum: Read Less [-]

INFO 294 Doctoral Research and Theory Workshop 2 Units

Terms offered: Spring 2024, Spring 2023, Spring 2022 An intensive weekly discussion of current and ongoing research by Ph.D. students with a research interest in issues of information (social, legal, technical, theoretical, etc.). Our goal is to focus on critiquing research problems, theories, and methodologies from multiple perspectives so that we can produce high-quality, publishable work in the interdisciplinary area of information research. Circulated material may include dissertation chapters , qualifying papers, article drafts, and/or new project ideas. We want to have critical and productive discussion, but above all else we want to make our work better: more interesting, more accessible, more rigorous, more theoretically grounded, and more like the stuff we enjoy reading. Doctoral Research and Theory Workshop: Read More [+]

Prerequisites: PhD students only

Fall and/or spring: 15 weeks - 2 hours of workshop per week

Additional Format: Two hours of workshop per week.

Doctoral Research and Theory Workshop: Read Less [-]

INFO 295 Doctoral Colloquium 1 Unit

Terms offered: Fall 2024, Fall 2023, Spring 2023 Colloquia, discussion and readings designed to introduce students to the range of interests of the school. Doctoral Colloquium: Read More [+]

Prerequisites: Ph.D. standing in the School of Information

Fall and/or spring: 15 weeks - 1 hour of colloquium per week

Additional Format: One hour of colloquium per week.

Doctoral Colloquium: Read Less [-]

INFO 296A Seminar 2 - 4 Units

Terms offered: Fall 2024, Spring 2024, Fall 2023 Topics in information management and systems and related fields. Specific topics vary from year to year. Seminar: Read More [+]

Prerequisites: Consent of instructor

Fall and/or spring: 15 weeks - 2-4 hours of seminar per week

Additional Format: Two to Four hours of Seminar per week for 15 weeks.

Seminar: Read Less [-]

INFO 298 Directed Group Study 1 - 4 Units

Terms offered: Fall 2019, Spring 2016, Fall 2015 Group projects on special topics in information management and systems. Directed Group Study: Read More [+]

Credit Restrictions: Students will receive no credit for INFO 298 after completing INFOSYS 298.

Fall and/or spring: 15 weeks - 1-4 hours of directed group study per week

Summer: 8 weeks - 1.5-7.5 hours of directed group study per week

Additional Format: One to four hours of directed group study per week. One and one-half to seven and one-half hours of directed group study per week for 8 weeks.

Directed Group Study: Read Less [-]

INFO 298A Directed Group Work on Final Project 1 - 4 Units

Terms offered: Spring 2022, Spring 2016, Spring 2015 The final project is designed to integrate the skills and concepts learned during the Information School Master's program and helps prepare students to compete in the job market. It provides experience in formulating and carrying out a sustained, coherent, and significant course of work resulting in a tangible work product; in project management, in presenting work in both written and oral form; and, when appropriate, in working in a multidisciplinary team. Projects may take the form of research papers or professionally-oriented applied work. Directed Group Work on Final Project: Read More [+]

Prerequisites: Consent of instructor. Course must be taken for a letter grade to fulfill degree requirements

Additional Format: One to four hours of directed group study per week.

Directed Group Work on Final Project: Read Less [-]

INFO 299 Individual Study 1 - 12 Units

Terms offered: Fall 2023, Summer 2016 8 Week Session, Spring 2016 Individual study of topics in information management and systems under faculty supervision. Individual Study: Read More [+]

Fall and/or spring: 15 weeks - 1-12 hours of independent study per week

Summer: 8 weeks - 2-22.5 hours of independent study per week

Additional Format: Format varies.

Individual Study: Read Less [-]

INFO 375 Teaching Assistance Practicum 2 Units

Terms offered: Spring 2024, Fall 2021, Fall 2020 Discussion, reading, preparation, and practical experience under faculty supervision in the teaching of specific topics within information management and systems. Does not count toward a degree. Teaching Assistance Practicum: Read More [+]

Fall and/or spring: 15 weeks - 2 hours of lecture per week

Additional Format: Two hours of lecture per week.

Subject/Course Level: Information/Professional course for teachers or prospective teachers

Instructor: Duguid

Teaching Assistance Practicum: Read Less [-]

Contact Information

School of information.

102 South Hall

Phone: 510-642-1464

Senior Director of Student Affairs

Siu Yung Wong

[email protected]

Senior Director of Admissions

Julia Sprague

[email protected]

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PhD In Management Information Systems

Program Overview

The PhD in Business Administration with a focus in Management Information Systems is a five-year full-time program. Consistently ranked among the best information systems PhD programs worldwide, the program is known for its cutting-edge research and support from actively publishing faculty.

The program prepares future information systems academics by providing strong foundations in a broad range of methods spanning psychometrics, econometrics, computational, design, and qualitative and by providing a strong emphasis in theory development to address important business and societal problems.

Given that information systems are ubiquitous and influence every aspect of life — individuals’ personal and work life, their transactions and interactions, organizational processes, outcomes, and interorganizational relationships, online platforms, markets, governments and society — the information systems field is broad and interdisciplinary and affords research opportunities across a diverse range of topics.

The research approach in the program is problem-focused, theory-based, and method-inclusive (i.e., all methods are welcome and no one single method is favored). Our PhD program provides you with significant individual flexibility, while at the same time ensuring you acquire the necessary conceptual and methodological skills to become a scholarly leader in our field.

Priority deadline: January 4

Applications after January 4 will also be considered until spots are filled

• C.Herman and Mary Virginia Terry Distinguished Chair of Business Administration, UGA Distinguished Research Professor and Professor , Department of Management Information Systems

Why a PhD in MIS?

There are five compelling reasons to join our program:

Research Productivity

We are among the most research-productive groups, consistently ranked in the top 10 or top 15 departments worldwide in publications in the top two IS journals ( MIS Quarterly and Information Systems Research ). Further, several of our faculty have won multiple research grants and awards for outstanding research.

Internationally Renowned Faculty

Our faculty includes a former president of the Association for Information Systems (Richard Watson), two Leo Award winners — the highest award in the field (Richard Watson and Elena Karahanna) — and three AIS Fellows (Richard Watson, Hugh Watson and Elena Karahanna).

Editorial Appointments

Our faculty includes current and former senior editors at MIS Quarterly , Information Systems Research , and the Journal of the Association for Information Systems , associate editors at MIS Quarterly , Information Systems Research , Management Science , and the Journal of the Association for Information Systems , and editorial board members of the Journal of Management Information Systems and Strategic Management Journal , among others.

Weekly Research Seminars

In these weekly seminars top scholars from around the world present and discuss their research. The PhD students have the opportunity to interact and discuss their research with these scholars in a meeting after the seminar.

Student Focus

Our culture is collaborative and supportive and one in which we view our students as junior colleagues. Students are provided extensive mentoring, support, and personal attention given our one-to-one faculty-student ratio. Evidence of the quality of mentoring is the outstanding placement of doctoral students and the plethora of journal papers co-authored with our faculty (over 100 publications in the past 10 years). Students can work with multiple faculty, not just their dissertation chair as they develop as scholars.

Typical Course Sequence

• MIST 9700 : IS Research Fundamentals
• MIST 9770 : Research Methods
• MIST 9760 : Foundational IS Theories and Emerging IS Phenomena
• MIST 9780 : Workshop & MTP
• Multivariate Statistics
• MIST 9750 : User Behavior and Technology Innovation 1
• MIST 9777 : Big Data Research Methods
• MGMT 9620 : Econometrics for Strategic Management
• GRSC 7770 : Teaching Seminar
• MIST 8990 : Directed Study
• First Year Exam (May)
• First Year Summer Paper due (beginning of Fall Semester)
• MIST 9790 : Combining Machine Learning and Econometrics
• MGMT 9610 : Introduction to SEM
• MIST 9710 : Digital Strategy and Digital Innovation 1
• MIST 9740 : Qualitative Research Methods
• Research Methods Elective
• Written & Oral Prelims
• Second Year Summer Paper due (beginning of Fall Semester)
• MIST 9000 : Doctoral Research
• Dissertation Proposal Defense
• MIST 9300 : Doctoral Dissertation 
• MIST 9300 : Doctoral Dissertation
• MIST 9300 : Doctoral Dissertation
• Dissertation Defense 2
• MIST 9750 and MIST 9710 are offered every other year. Some incoming PhD student cohorts will take MIST 9750 in their first year and MIST 9710 in their second year and others will take MIST 9750 in their second year and MIST 9710 in their first year.  ↩︎
• Dissertation defense occurs in the spring of their fifth year.  ↩︎

Our PhD graduates are placed in top research universities around the world.

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Program and Course Information

A research-based approach.

The PhD in IS is a research-based program that takes a broad perspective, favoring an approach in which the impact of IS on organizations and society is examined from multiple perspectives, including, but not limited to, organizational theories.

While the program is designed for students interested in an academic career, the structure of the program is useful for students interested in teaching and research positions outside of academia as well.

The program is designed for face-to-face learning.

The Baylor IS PhD curriculum focuses on educating you on both the positive and negative consequences of IS and the moral and ethical dilemmas IS introduce into society.

The PhD curriculum will expand your theoretical horizons through a cross-disciplinary approach that will broaden your understanding of IS. This approach allows you to take a portion of your courses outside the IS Department.

You will have the opportunity to take courses that correspond to your research interest spanning various academic fields including philosophy, sociology and statistics.

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That's the DSU equation. We're a four-year university with nationally recognized programs, cutting-edge facilities, and the brightest thinkers. But we're also a tight-knit, inclusive community. Small class sizes mean hands-on training and individualized attention. All this with an affordable, public school price that's among the best values in the region.

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Information Systems Doctor of Philosophy (PHDIS)

Information systems level: expert.

Master, develop, and support new IT innovations with a flexible doctoral program. Online, on-campus, part-time or full: it's your call.

This gratifying degree prepares you for a career in research, teaching, or administration. Choose from three specializations: analytics, security, or health care. 

Take courses that address the most contemporary issues in the field. Utilize prevalent technologies. Comprehend Information Systems (IS) literature and demonstrate an understanding of milestones and seminal works of leading researchers. Graduate with an intricate understanding of IS theory and practice, qualitative design, and quantitative research techniques.

Additionally, you'll have the opportunity to conduct research and produce a written dissertation focused on cutting-edge information systems.

The DSU difference

Since technology is embedded in everything we do, you'll be on the right path to becoming an ideal leader in IS. Our PhD in Information Systems program has a multi-disciplinary focus and a practical emphasis on applying IS to organizations and management systems. 

Quick facts

Credits:   72   | delivery:  online, on campus, hybrid   | start terms:   fall, spring.

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College of Business and Information Systems

Shape the future of the IS field

The College of Business & Information systems is based in East Hall, the second oldest building on campus, but the programs of study prepare students to make an impact on the future through careers in business, information systems, data analytics, and health information and informatics, and artificial intelligence for organizations.

College of Business & Information Systems students have opportunities to participate in research projects, and learn from their fellow students’ research projects.

Extra-curricular activities give students the chance to apply their classroom knowledge in national competitions, take advantage of networking events, and to give back to their community.

Technology is at the heart of DSU's mission. As a Center of Excellence designated by the National Security Agency and The Department of Homeland Security, there’s really no better place to pursue advanced study.

We infuse our PhD curriculum with the latest advances in IS. You'll graduate as an in-demand expert in your specialization. Coursework includes theory and practice, qualitative design, and quantitative research techniques, and more.

Learn, lead, innovate

Study a broad range of topics and problems before choosing a specialization. Refine your expertise and develop unique research interests. Our graduates are poised for rewarding careers in academia, government, finance, and business. 

• University professor
• Academic researcher
• Government or corporate researcher
• IS director in business or finance

“The PhDIS program at DSU will enable me to research best practices and techniques of system design and data management, to support school counselors and advance both the school counseling and IS field.” Kalee Crandall PhDIS - '24

Learning outcomes

Upon completion of the PhD degree in Information Systems, students will:

• Be able to demonstrate a broad and comprehensive understanding of core knowledge and fundamental practices in information systems
• Be able to demonstrate conceptual knowledge and ability to utilize prevalent technologies of information systems
• Be able to demonstrate a highly developed knowledge of information systems literature, particularly in their area of specialization
• Be able to demonstrate a scholarly understanding of milestones and seminal works of leading researchers in their area of specialization
• Be able to demonstrate an understanding of information systems research methods and an ability to conduct research and evaluate research results
• Be able to effectively formulate, communicate, present and defend the results of their research and any conclusions drawn from it

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Spartan Alert

Information systems, ph.d..

FULLY ONLINE PROGRAM AVAILABLE

The Doctor of Philosophy in Information Systems program is designed to prepare students for careers as members of faculty in academic information systems units as well as careers in non-academic research and professional organizations.

Program Distinctions

• This program provides training in basic and advanced information systems theory and practice so that students master the technical and conceptual tools needed for conducting high-quality information systems research. 
• Advanced, specialized training is provided in a number of information systems disciplines, such as enterprise resource planning, global information technology, information resource management, artificial intelligence, data mining, data warehousing, e-commerce, knowledge management, and supply chain management. Students acquire expertise that can be applied in a wide range of academic, government, and private sector environments.
• Current students in this program have an average of two papers published in top journals including Journal of Computer Information Systems (JCIS), Communications of the Association for Information Systems (CAIS), Information and Management (I&M), and Journal of Information System Security (JISSec).

The Student Experience

Students conduct structured and supervised research experiences so that they can develop the technical, conceptual, and communication skills required to conduct high-quality, independent research.

After Graduation

Recent graduates were invited by some top universities for faculty positions including Florida International University, James Madison University, University of Massachusetts Amherst, and the University of Toledo, among others.

Want more information? Let’s get started!

Program details.

Degree Type: Doctoral

College/School: Joseph M. Bryan School of Business and Economics

Program Type: Majors & Concentrations

Class Type: In Person,Online

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Dr. Al Salam Graduate Program Director [email protected] 336-256-8589

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The PhD program in information systems (IS) prepares students for an academic career of scholarly research and university-level teaching.

From studying human-computer interaction, online reviews and social media design, to IS implementations and strategy, doctoral students explore real-world IS problems using a variety of methods, including surveys, experiments, archival data analysis , and analytics.

Message from the Coordinator

The Information Systems (IS) PhD takes a theory-inspired and practice-engaged approach to research, in order to understand how individuals, organizations and communities develop, design, use, and are affected by, information systems. We want our doctoral students to investigate relevant and interesting IS phenomena grounded in the IS discipline, and be intellectually curious, rigorous, critical and creative in their approach to research problems and research designs.

Research in our program targets the intersection of (1) implementation, design, and use of information systems, and (2) business and societal domains of their application, to produce research that can make a difference to theory, and practice and/or policy making. Our faculty’s research encompasses on a variety of technologies (e.g., ranking algorithms, social media and AI applications), domains of application (e.g., online communities and algorithmic work), and methods (experiments, secondary data analysis, surveys) . Our course work focuses on a strong theoretical and methodological foundation in the IS discipline, combined with an understanding of how IS are applied to the pressing issues of our time. We investigate research problems that can make a difference to organizations and/or society, bringing to bear methods that combine the power of different kinds of data. Our goal is to develop outstanding researchers and teachers who will make substantive contributions to scholarship and knowledge creation, and to place them in academic research institutions.

Our doctoral program is successful because it offers:

• World-class faculty who actively research, publish and shape-steer the scholarship in the top IS journals
• Collaborative and creative intellectual community that supports doctoral student scholarly development
• Comprehensive, rigorous and relevant coursework that equips students with the theories, concepts and methods needed to investigate IS problems
• Individual attention from multiple faculty members to support students in early research endeavors and multiple publication opportunities
• Preparation for the IS academic job market
• Exposure to the IS research community from around the world through support for traveling to international conferences (AMCIS, ICIS, HICSS, ECIS, etc.) and on-campus research talks

We welcome applications from individuals who have a strong academic record, are eager to investigate, why and how IS are developed, deployed and used, and aim to pursue a scholarly career in academia. Relevant industry experience can be an advantage, but it is not a must.

Monideepa Tarafdar Charles J. Dockendorff Endowed Professor and PhD Coordinator in Information Systems

The PhD program in information systems (IS) prepares students for an academic career of scholarly research and university-level teaching. From studying human-computer interaction, online reviews and social media design, to IS implementations and strategy, doctoral students explore real-world IS problems using a variety of methods, including surveys, experiments, archival data analysis, and analytics.

Teaching instruction is provided, and students are provided with teaching opportunities to support their development as world class business instructors.

Our program offers access to a unique group of world-class faculty who conduct research in the following areas:

• Human-computer interaction; decision support systems and online decision-making
• Website design and signaling; Online consumer impulsiveness; B2C electronic commerce strategy
• Social media affordances; online reviews; ranking algorithms
• Societal impacts such as social media driven online activism and social protest
• Algorithms, AI, bias and transparency
• IS use and post-adoptive cognitions, emotions, and behaviors (both negative and positive)
• Big data analytics use and strategy
• IS and wellbeing
• Healthcare systems implementation and use

Students generally complete a PhD in Information Systems within 4-5 years, beginning their studies in the fall semester. Students must take 45 credits of coursework, building foundational knowledge in information Systems and Research Methods before taking minor and elective courses. The program includes a first year core exam (summer paper); a comprehensive examination generally taken after completing the second year; a 3-course teaching requirement and a dissertation.

Research in information systems draws from a number of fields including psychology, sociology, human-computer interaction, computer science, marketing, management and sociology.  Topics of study include:

• Theories and concepts in the IS discipline
• Research methods (experiments, surveys, big data analysis, statistics, econometrics)
• Domains in the IS discipline (e.g. Human-computer interaction, post adoptive use, negative psychological, behavioral and societal effects of IS, algorithmic work, artificial intelligence and related concepts, social media driven phenomenon and online communities)
• Theories in psychology, management and sociology

YEAR 1: Coursework, including core courses; Core exam (summer paper)

YEAR 2: Coursework, including core courses, research electives and minor area courses; Comprehensive exam

YEAR 3: Development of dissertation proposal; Teaching; Additional coursework as needed;

YEAR 4-5: Dissertation; Teaching

IS Doctoral Candidates

Information Systems & Technology

PhD in Information Systems & Technology

With built-in flexibility to accommodate working professionals in Information Systems & Technology, our PhD in program prepares you to conduct relevant IS&T scholarship and make lasting contributions to the academic research community.

The PhD program maintains a design-centric emphasis that focuses on solving pragmatic problems using a mixture of creative designs and existing theory. Technical courses provide the requisite skills to develop these IS&T solutions. Spanning applications in education, health, government, business, and more, our curriculum trains candidates to develop the research and analytical skills to evaluate the effectiveness of designed solutions and their impact on improving human performance and addressing societal challenges. Five available concentrations allow students to customize a track of study that best aligns with their interests and career aspirations while providing a flexible curriculum and schedule that accommodates both full-time students and working professionals.

Program Highlights

• Data Science Lab
• Advanced GIS
• Social Learning
• You can pursue a PhD in Information Systems & Technology in conjunction with another degree program at CGU, such as an MA in Public Policy. You earn a diploma for each degree, “double count” some units from one program to the other, and decrease your required total units.
• Our GIS Club convenes students and professionals interested in geographic information systems (GIS) and informs the local community about the latest GIS workshops and conferences.
• This program is STEM designated, allowing international students who hold F-1 visas to apply for OPT work authorizations for a total of 36 months (an initial 1-year period and a 24-month OPT STEM extension) of paid work experience in the U.S. after graduation.

Program At-a-glance

required units

degree awarded

Spring, Summer, Fall

program start

4-7 years | full time*

estimated completion time

Areas of Concentration

Data science & analytics.

Explore how massive volumes of data can be used to solve business and societal problems through data mining, specialized programming, and other computational skills.

Cybersecurity & Networking

Develop a fresh perspective on cyber threats, hacker motivations, modern attack patterns, and next-generation mitigation solutions.

IT Strategy & Innovation

Study current IT innovations, key business strategies for internet entrepreneurs, and how to create a successful Internet startup.

Geographic Information Systems

Learn to develop transformative GIS solutions for organizations and companies through geographic data mapping, location-based services, and related technologies.

Health Informatics

Study the relationship between information technology and health care services through a unique partnership with the School of Community and Global Health.

Where You Can Find Our Alumni

NASA Jet Propulsion Lab

Cal Poly Pomona

Northrop Grumman Aerospace Systems

California Institute of Technology

University of California, Riverside

City of Hope Hospital

Samir Chatterjee

Fletcher Jones Chair of Technology Design & Management

Research Interests

Design science research, Health informatics, Electronics and telecommunication engineering

Professor of Information Systems & Technology

Management information systems, Programming, Software development, Research methods, Statistics

Associate Professor of Information Systems & Technology

Data science, Machine Learning, Natural Language Processing, Health Informatics, Mobile Health, Data Management, Data warehousing, Business intelligence, ICT4D

Tamir Bechor

Research Fellow

Cybersecurity, IT leadership and management

Chinazunwa Uwaoma

Research Assistant Professor of Information Systems & Technology

Internet of Things, Mobile Computing, Computer Communications & Networks, Healthcare Systems, Artificial Intelligence, and Cyber Security

Wallace Chipidza

Assistant Professor of Information Systems & Technology

Dynamics of social networks, Quantum Computing and Applications, Internet Privacy, ICT4D

Additional Program Requirements

Research Tools Requirement

• Primary Text Language
• Secondary Research Language: Research Tool

Qualifying Portfolio The Qualifying Portfolio compiles activities that reflect your ability to succeed as a PhD candidate. Although you will work with your faculty advisor to create a portfolio customized to your needs, there are five required items:

• A refereed paper published in the proceedings of a conference
• A refereed journal article that has been published, accepted for publication, or revised and resubmitted with the student as a primary author
• One grant proposal, consulting engagement, or related practice
• Post-secondary teaching or mentoring
• Service as a peer reviewer

PhD Completion

• PhD qualifying exams
• Dissertation proposal
• Dissertation and oral defense

Partnerships

Esri Claremont Graduate University’s comprehensive partnership with Esri, the world’s leading supplier of geographic information systems (GIS) software, offers numerous benefits, including:

• Scholarships for Esri employees
• The Esri Development Center enables CGU students and faculty to teach and develop state-of-the-art applications in the university’s Advanced GIS Lab
• GIS training and student recognition through an Esri-sponsored annual achievement award

Microsoft Developer Network Academic Alliance CISAT is also a Microsoft Developer Network Academic Alliance Member, which gives our students and researchers access to the latest technologies for use in classroom assignments and projects.

IBM Watson Analytics Academic Program To ensure students work with leading data analytics technologies, CISAT is part of the Watson Analytics Academic Program (WAP), which provides no-cost use of IBM® Watson Analytics software for classroom teaching and research

Application Guidelines

Key Dates & Deadlines

CGU operates on a priority deadline cycle. Applicants are strongly encouraged to submit complete applications by the priority dates in order to assure maximum consideration for both admission and fellowships.

Once the priority deadlines have passed, the University will continue to review applications for qualified candidates on a competitive, space-available basis. The final deadlines listed are the last date the University can accept an application in order to allow sufficient time to complete the admissions, financial aid, and other enrollment processes.

Spring 2025 Priority Deadline – November 1, 2024 Final Deadline (International) – November 15, 2024 Final Deadline (Domestic) – December 1, 2024 Classes begin – January 21, 2025

Summer 2025 Priority Deadline – February 1, 2025 Final Deadline (International) – March 1, 2025 Final Deadline (Domestic) – April 1, 2025 Classes begin – May 19, 2025

Fall 2025 Priority Deadline – February 1, 2025 Final Deadline (International) – July 5, 2025 Final Deadline (Domestic) – August 1, 2025 Classes begin – August 25, 2025

ESTIMATED TUITION (CALIFORNIA RESIDENTS, NON-RESIDENTS, INTERNATIONAL)

*Based on 2024-2025 tuition rates.

STUDENT FEES (PER SEMESTER)

For estimates of room & board, books, etc., please download CGU’s  Cost of Attendance 2024-2025 .

Review General Costs

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Ph.D. in Computing and Information Systems, SIS Track

Our Ph.D. in Computing and Information Systems program is uniquely designed to train Ph.D. students in innovative, interdisciplinary research of societal relevance centered on computing and informatics. It is the largest and fastest growing Ph.D. program on campus. It is staffed with a strong faculty of international stature and ranked in the top 10 in faculty productivity among 375 top research universities in the US in 2017.

Research funding is from major federal agencies, including NSF, NIH, DOD, DOE, DHS, ARO, etc. The program also receives funding from the Department of Education.

For more information, or if you have questions about the SIS track, email: [email protected]

Information Systems

Effective solutions for complex business problems..

Simon’s PhD in Information Systems focuses on the business aspects of Information Technology use and management, and the analytic and quantitative tools and techniques to address them. The research conducted by the students and faculty has significantly advanced the state of the art in research on information systems in general, with an emphasis on information systems economics and machine learning modeling.

Meet IS Faculty

Prepare with Math Camp.

Program outline: information systems, the first year.

The first year provides students with a strong methodological foundation in order to prepare them for research in the advanced years of the program. Students are required to take courses offered by Simon Business School as well as the University of Rochester. First year students are required to pass Preliminary Requirements by demonstrating proficiency in specific courses. A research-oriented first-year paper is due August 31 of the start of the second year.

The Second Year

The second year deepens students' knowledge of Information Systems. Students work in conjunction with the faculty to write two papers on two individual research topics. These papers are due by May 31 of the second year. Students are also required to write a Qualifying Exam paper, due by November 30 of the third year. This paper is usually a more in-depth version of one of the two papers used for the second-year papers requirement.

The Third Year and Beyond

Students will take additional courses in the third year after passing the Qualifying Exam. Students also begin work on a dissertation. Research in the field of Information Systems focuses on problems of design, performance analysis, and optimization of information systems.

Required Courses.

The Course Catalog contains degree requirements and course descriptions. Please refer the Simon Registrar's website for the current Course Catalog.

Simon Registrar

Course Catalog

PhD Information Systems Courses

This course introduces important research methods/topics for IS researchers, covering analytical modeling, causal inference, and machine learning. For analytical modeling, we will discuss auction and mechanism design for information/ computation goods. For causal inference, we will establish the probabilistic foundation of commonly used methods such as DID, matching, IV, and regression discontinuity. For machine learning, we will introduce the statistical learning theory, SVM, EM, MCMC, variational inference, and deep learning.

This course introduces students to research in Information Systems (IS) and Operations Management (OM). Multiple lectures will be dedicated to each topic, covering the necessary mathematical background, primary analysis techniques, and important, seminal, or recent papers within each area. The course aims to attain the following objectives: learn about what constitutes research in IS and OM, develop critical thinking about academic papers, familiarize students with new research areas, provide opportunity to think about new research problems, and practice constructing and delivering academic talks.

Department of Information Systems

Select Section

PhD program overview

The PhD in Business Administration with a concentration in Computer Information Systems from the W. P. Carey School of Business will prepare you for a career at leading research universities.

This full-time doctoral program develops your capability to review, analyze, conduct and publish research in top journals through a series of seminars and additional supporting coursework. You will also participate in ongoing research projects with faculty members in the Department of Information Systems and other W. P. Carey departments, as well as faculty members in other ASU schools and colleges.

The size of the Department of Information Systems doctoral program is about ten students. We seek to admit two students per year.

Students in the program have published in top journals such as Management Science , Information Systems Research , Journal of Operations Management , among others.

Department of Information Systems Office: BAC 601 Phone: 480-965-3252 Fax: 480-727-0881 [email protected]

Information Science, PhD

In an era where digital technologies shape human interaction and cultural expression, understanding their workings, impacts and uses is crucial. Delving deep into these pivotal issues allows for innovation, critical thinking and enhanced digital literacy.

Master Information Science Challenges

The Information Science PhD program equips you with advanced quantitative and qualitative research skills, preparing you to address complex information challenges faced by modern society and organizations. The field of information science evolves rapidly. This program offers extensive opportunities for future scholars to explore critical research questions and enhance their professional goals.

Making History

Monica Rogers achieved a significant personal milestone by becoming the first graduate of the University at Buffalo's online PhD in Information Science program. Balancing her career while focusing on data visualization literacy, Rogers exemplifies the program's flexibility and support for diverse professional paths. Her success story underscores the program's ability to cater to working professionals and highlights the innovative research being conducted by its students.

Points of Distinction

This program offers a unique one-week annual residency that allows students to engage with peers and faculty, fostering invaluable connections and hands-on learning opportunities outside of the online environment.

The online Information Science doctoral program is one of only two in North America, offering a unique pathway to advanced knowledge and career advancement.

Benefit from a curriculum specifically designed to address the rapid and ongoing changes in the information science field, ensuring you stay at the forefront of this dynamic discipline.

Program Overview

Program Coursework

The program coursework is designed to prepare you for next steps. Students who complete this program successfully :

• have a broad understanding of the theories of information science, as well as theories from cognate disciplines which have been applied in information science.
• have a broad understanding of qualitative and quantitative methods, which are commonly applied in information science research.
• demonstrate deep and broad knowledge of one or more domain topics within information science.
• demonstrate the ability to execute research in their domain area using appropriate methods and theory.

Master's Degree (30-36 credits)

Upon acceptance into the doctoral program, you are allowed to transfer credits from your master's degree program.

Core Courses (14-18 credits)

LIS 601 Qualitative Methods in Information Science LIS 602 Quantitative Methods in Information Science LIS 603 Theoretical Foundations of Information Science LIS 604 Statistics I LIS 605 Statistics II

Electives in Discipline (9 credits)

Specialization will occur through elective courses and, where appropriate, independent study elective courses.

You will work with your advisor to assemble a dissertation committee conforming to UB graduate guidelines. The committee composition must reflect the intellectual diversity of the Department of Information Science, and must be approved by the director of the PhD program. The committee may include one external member.

You will decide on a research topic and produce a short research proposal (dissertation prospectus) that includes the research questions to be pursued; a short literature review; a description of one or more possible theoretical frameworks that will inform the research; and a summary of the methods expected to be applied. Your research proposal is expected to be approximately 20 pages in length.

You will pass an oral examination on the background knowledge required to conduct the research in your proposal. The committee will provide a written list of topics to be covered in the examination. This requirement must be met no later than the end of the fourth semester in the program (for full-time students). Upon successful completion of the oral examination, you may file for candidacy.

Qualifying Requirements

Dissertation (12-18 credits).

The final dissertation will be a refinement and expansion of the your dissertation prospectus. Your final dissertation must be completed by the end of the sixth semester in the program (for full-time students). You will defend your fully publication-ready dissertation at a public defense that will include an oral examination by your PhD committee.

Application Requirements

In an effort to make the application process more equitable, the GRE/MAT is no longer required for admissions consideration. If you still plan to take the GRE/MAT exam, you can send your scores through the testing agency, and they will automatically be added to your application; however, they are not required for admission consideration to this program.

You must have a bachelor's and master's degree. 

We have a small program that values strong faculty and student relationships. Before applying, explore our faculty’s research interests by viewing our Research Centers, Institutes and Profiles  and Faculty Directory . Feel free to contact faculty with similar interests to yours to see if they are taking on new students. If you are unsure who to contact, Program Director Dr. Amy VanScoy ( [email protected] ) is happy to discuss your interests and recommend faculty to talk to.

Submit your completed online application, which includes:

• Application fee:  A $50 non-refundable application fee, submitted electronically through UB's ePayment system.
• Contact information for at least three individuals  who will each be asked to provide an electronic recommendation letter. You should ask individuals who can assess your achievements and potential as a student and a researcher. If there is no individual who can evaluate your achievements as a student, you may want to enroll in a course, such as LIS 575: Research Methods. The prof for this course could serve as an academic reference for your application.
• Unofficial transcripts  from all colleges attended. (UB transcripts are automatically submitted for current UB students and alumni.)
• Sample of academic writing  (e.g., article, essay, thesis)
• Statement of research interest: The statement of research interest should be a concise statement about your academic and research background and future interests. Please be specific in explaining how the course offerings and faculty expertise of this program fit your educational and career objectives. Be sure to include the specific faculty you would like to work with and why. We consider a 1000-word statement as an appropriate length. Finding the right doctoral program requires that doctoral candidates specify and describe their research interests so they can evaluate whether there is a good fit between what they want to study and faculty research expertise. Start by reviewing our faculty directory and faculty web pages and once you are familiar with faculty research areas, read some of the faculty publications that you find most interesting. That will help you determine if there is a good fit between your scholarly interests and what our faculty members are currently researching. Everyone knows that grade point average and letters of reference are important in the decision-making process; however, alignment with faculty research interests and the academic program can often be a determining factor in admission decisions.
• Statement of educational and career goals: The statement of educational and career goals should outline your reasons for applying to this program. Please include a candid analysis of your long- and short-term professional objectives and indicate how this program will help you achieve your objectives. Your statement should be at least one to two pages in length.
• Resume or CV

Faculty Interview:  After applications are submitted and reviewed, qualified candidates will be contacted for an admission interview with the faculty.

Former/Maiden Name:  Please provide us with your former/maiden name if you have one. When requesting transcripts, please ask the sending institution to indicate your current name and former/maiden name.

Admission Decision: The admission decision will be communicated to you as soon as review is complete. The decision is based on a number of factors and is the result of a thorough and deliberate process. All decisions are final and cannot be appealed.

In-State Residency Tuition

In order to qualify for the in-state residency tuition rate, you must provide residency documentation indicating you have lived in New York State (NYS) 12 months before your semester start date.

If accepted, you will need to upload three documents to qualify for the in-state tuition rate. See  Required Documents for Residency Application  for more information. 

International Applicant Additional Requirements

• Official original proof of your degree
• A copy of your passport biographical page
• TOEFL minimum score is 250 for computer-based test, 600 for paper-based test and 79 for internet-based test
• IELTS Academic Test minimum score is 6.5 overall
• PTE minimum score is 55 overall
• DET minimum score is 120 overall
• Financial documentation:   International graduate applicants must document their ability to pay for all costs incurred while studying in the U.S.
• An official bank statement

All financial forms and supporting documentation with required signatures must be uploaded with your application and dated within one year of your intended enrollment date.

Career Opportunities

Graduates of our program become:

• Faculty/scholars of information science at a university
• Researchers at a profit or nonprofit organization
• Senior managers of a large public library
• Senior managers of a university campus library

Program Faculty

Samuel Dodson

Assistant Professor Information Science

Department of Information Science Graduate School of Education University at Buffalo 524 Baldy Hall (North Campus) Buffalo, NY 14260–1000 Buffalo, NY 14260

Phone: 716-645-1488

Email: [email protected]

Africa S. Hands

Buffalo, NY 14260

Phone: 716-645-1412

Email: [email protected]

Saguna Shankar

Department of Information Science University at Buffalo 549 Baldy Hall (North Campus) Buffalo, NY 14260–1000 Buffalo, NY 14260

Phone: 716-645-1481

Email: [email protected]

Amy VanScoy

Associate Professor Information Science

546 Baldy Hall North Campus Buffalo, NY 14260

Phone: 716-645-1487

Email: [email protected]

Jianqiang Wang

528 Baldy Hall North Campus Buffalo, NY 14260

Phone: 716-645-2412

Email: [email protected]

Brenda L. Battleson White

Clinical Associate Professor Information Science

545 Baldy Hall North Campus Buffalo, NY 14260

Phone: 716-645-1486

Email: [email protected]

Graduate Assistantships

Assistantships are available in a variety of areas that change from year to year. Compensation for positions ranges from hourly pay only to a stipend to tuition remission plus a stipend. Generally, assistantships require 20 hours of work per week. The application process for assistantships is separate from the program admission process. Assistantship opportunities are posted for the following academic year in mid-January, from offices on campus such as Campus Living, Career Services, Student Engagement, Intercultural and Diversity Center, among others. While assistantships are limited, new opportunities become available throughout summer and into the fall semester.

Enhancing Diversity in Librarianship

Major grant secured to improve retention of underrepresented librarians..

Amy VanScoy, an associate professor of information science at the University at Buffalo, is spearheading a $478,000 grant-funded project to boost retention of underrepresented librarians. Her research, conducted alongside East Carolina University's Kawanna Bright, examines the experiences of BIPOC librarians and aims to address issues like isolation and discrimination. VanScoy’s initiative seeks to foster a more inclusive library profession by leveraging survival analysis techniques and updating past datasets to reflect diverse identities. Learn more about her impactful work here .

Faculty Expertise

How can libraries demystify the admission and college-going experience for undergraduate and graduate students? After a career in admissions, academic advising and library science, that’s the question that Assistant Professor of information sicence Africa Hands seeks to answer. Through her research, she aims to improve access to and awareness of information, resources and services that move people toward their personal, professional and community goals. Her scholarship focuses on the doctoral student experience, the cultural and social capital of first-generation students, and public library support for college-bound patrons.

• Computer Science (Ph.D.)

Demonstrate mastery in several areas of computer science and make an original contribution to research in the field as a Ph.D. candidate in computer science.

• Academic Programs

Pursue an academic or industrial research career through this doctoral program.

Coursework revolves around seven core groups: theory of computation, systems, programming languages, networks and security, databases, software engineering, and computational intelligence. The amount of coursework is dependent on previous degrees earned.

Passing a written and oral qualifying exam, comprehensive exam, and defending a thesis is expected. A thesis research problem must be presented and defended to a committee of faculty at the comprehensive exam. Learn more about our research   areas .

Located just minutes from downtown Chicago, Illinois Tech’s Mies Campus offers easy access to the city’s resources. A growing number of tech companies are calling Chicago home. The city government is extremely open with its data, allowing and encouraging unusual access for unique research opportunities.

Lean more about our  current Ph.D. students , the labs where they conduct their work, and their research projects.

Program Overview

Coursework explores seven core groups: theory of computation, systems, programming languages, networks and security, databases, software engineering, and computational intelligence. Ph.D. candidates in computer science are expected to demonstrate mastery in these areas and to make an original contribution to research.

Career Opportunities

A research career in academia is attainable with a Ph.D. in computer science, although career opportunities in industry are also possible.

• Computer scientist
• Computer systems engineer
• Computer science professor
• Computer network architect
• Research and development

View Details

Admission Requirements

The minimum standards for admission to the computer science Ph.D. program are:

• A four-year bachelor’s degree in computer science for the Direct program, or a master’s degree in computer science is required. Applicants must have a high GPA.
• GRE scores: For admission in 2023, GRE General scores are recommended for all Ph.D. applicants and required for applicants wanting to be considered for a teaching assistantship and all applicants with degrees from outside the U.S. For the Direct program, the minimum required GRE scores are 310 and 4.0 (analytical writing). For the post-master’s Ph.D. program, 304 and 3.5 are required. In addition, the GRE quantitative score must be at least 70%. The score should be at most 5-years-old.
• Proficiency in English. For applicants with degrees from schools where the primary language of instruction was not English, a minimum score of 70 on the internet-based TOEFL, 47 on the PTE, or 5.5 on the IELTS exam is required for admission consideration.
• Three letters of recommendation are required by the Department of Computer Science.
• A personal statement.
• Good academic standing is required for applicants who are currently pursuing a graduate degree at another university or in another department at Illinois Tech. Good academic standing should be confirmed by submitting a transcript for the final semester from the current university.

Research Areas

The world-class research pursued by Department of Computer Science faculty drives innovation in many fields of state-of-the-art computation. Learn more about the research opportunities in these areas:

• Artificial Intelligence and Machine Learning
• Cybersecurity
• High Performance and Parallel Computing
• PL, Compilers, and Software Engineering

Learn more...

Doctoral Degree in Computer Science

Carnegie Mellon's Ph.D. in Computer Science is, above all, a research degree. When the faculty award a Ph.D., they certify that the student has a broad foundation and awareness of core concepts in computer science, has advanced the field by performing significant original research and has reported that work in a scholarly fashion.

When you begin our Ph.D. program, you’ll take the Introductory Course for Doctoral Students — an intense two week program that orients you to the department, introduces you to research and education topics our faculty are interested in, helps you find a faculty advisor and familiarizes you with Carnegie Mellon’s resources. Next, you’ll gain a broad understanding of fundamental research issues in major areas of computer science through coursework and original research. Finally, you’ll write and orally defend a thesis that guarantees you understand the area well enough to advance the state of knowledge in the field.

During the first two years of the program, you’ll gain the foundation of knowledge that will allow you to become an expert researcher in computer science, primarily by

Mastering a body of graduate material, achieved by passing 96 university units worth of graduate courses (equivalent to eight full-time courses).

Learning how to organize and begin to carry out original research, achieved by participating in directed research.

You will also serve as a teaching assistant, hone your writing and speaking skills and maintain your programming prowess. You’ll also receive periodic evaluation of your progress, and must make satisfactory progress to continue in the program.

Time Commitment:

As a Ph.D. student in computer science at CMU, you'll spend roughly five years acquiring a body of technical knowledge that includes a familiarity with the breadth of the field, as well as a deep understanding of your research area. From your second month in the program, you'll work closely with your faculty advisor, who is charged with guiding your education and monitoring your progress through the program. You'll take courses, teach and perform directed research — all to ensure that you leave Carnegie Mellon as an expert in your field. For a complete breakdown of our program requirements, read our Ph.D. Handbook .

Financial Information:

The Computer Science Department offers all Ph.D. students full financial support while they are in good academic standing in their respective programs. To learn more about Ph.D. funding, visit the SCS  Doctoral Programs  webpage.

Graduate Tuition: https://www.cmu.edu/sfs/tuition/graduate/scs.html

Student Fees: https://www.cmu.edu/sfs/tuition/fees/index.html

Carnegie Mellon Graduate Student Financial Aid: https://www.cmu.edu/sfs/financial-aid/graduate/index.html

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Information Systems

Explore this course:.

Applications for 2024 entry closed at 5pm on Friday 6 September. Applications for 2025 entry open on Monday 16 September.

Information School, Faculty of Social Sciences

Course description

By the end of the course, you'll have an in-depth understanding of information systems within an organisational context, emphasising issues related to information, people, information technologies and the business environment. You'll have gained practical skills related to the design and analysis of information systems. Your knowledge and skills will be highly valued in industry, commerce and academia.

We have world-leading research groups in areas such as database systems, information retrieval, speech recognition, information extraction and information management. This means you'll not only gain knowledge of the well-established fundamentals, but also the most current and advanced theories and techniques.

The course focuses on core topics in information systems including information systems modelling, project management and the impact of information systems on organisations and society. These are complemented by practical skills in computer programming and the study of professional issues in computing.

You can then tailor the course to your own interests by choosing from more specialised topics including those with a more technical focus such as database design and human-computer interaction, or topics that focus on how information management can be used to benefit organisations through digital business and business intelligence.

Accreditation

CILIP accredited for the MSc award.

An open day gives you the best opportunity to hear first-hand from our current students and staff about our courses.

You may also be able to pre-book a department/school visit as part of a campus tour. Open days and campus tours

• 1 year full-time
• 2 years part-time
• 3 years part-time

A variety of teaching methods are used, combining lectures from academic staff and professional practitioners with seminars, tutorials, small-group work and computer laboratory sessions. There is strong emphasis on problem-solving and individual aspects of learning, with the expectation that you will engage in independent study, reading and research in support of your coursework.

Teaching consists of two 15-week semesters, after which you will write your dissertation.

Assessments vary depending on the modules you choose but may include essays, report writing, oral presentations, in-class tests and group projects.

There is also a dissertation of 10–15,000 words, which provides the opportunity, under one-to-one supervision, to focus in depth on a topic of your choice. You may choose to carry out your dissertation with an external organisation.

Your career

After completing the course, you'll be equipped to pursue a variety of roles across a wide range of industries.

Examples of organisations that have employed our graduates include:

• Fosun International
• Huawei Technologies
• Price Waterhouse Coopers
• China Unicom

Graduates are employed in roles such as:

• Product Manager
• Civil Servant
• Risk Associate
• Senior Analyst
• IT Project Manager Information
• System Auditor

Information School

The University of Sheffield Information School is ranked number one in the world for library and information management in the QS World University Rankings by subject 2024. These rankings are based upon academic reputation, employer reputation and research impact.

The school has been at the forefront of developments in the information field for more than fifty years. The subject is characterised by its distinctive, interdisciplinary focus on the interactions between people, information and digital technologies. It has the ultimate goal of enhancing information access, and the management, sharing and use of information, to benefit society.

When you come to study with us you'll be an integral part of our research culture. The school is your home and we pride ourselves on the friendliness and helpfulness of our staff.

We offer an outstanding academic education through a wide range of taught postgraduate degrees which embed the principles of research-led teaching.

When you join any of our degree programmes you'll develop a critical understanding of current issues in library and information management. You'll benefit from being taught by staff who are undertaking leading-edge research and who have many links with industry.

As part of our mission to provide world-quality university education in information, we aim to inspire and help you pursue your highest ambitions for your academic and professional careers.

Student profiles

The topics we studied felt topical and relevant to global issues

Hasnah Salem Patel Postgraduate student, MSc Information Systems

Salem came to Sheffield and got involved in all kinds of sporting and outdoor activities, whilst also getting immersed in the cutting edge content that the Information Systems course provided them.

Time flew by way too quickly. I will always cherish these beautiful memories.

Indian student Anirban moved to Sheffield from Kolkata and enjoyed Sheffield's small-town feel, whilst taking a mix of technical and non-technical modules on the Information Systems course.

Entry requirements

Minimum 2:1 undergraduate honours degree in any subject.

IELTS 6.5 (with 6 in each component) or University equivalent

If you're an international student who does not meet the entry requirements for this course, you have the opportunity to apply for a pre-masters programme in Business, Social Sciences and Humanities at the University of Sheffield International College . This course is designed to develop your English language and academic skills. Upon successful completion, you can progress to degree level study at the University of Sheffield.

If you have any questions about entry requirements, please contact the school/department .

Fees and funding

Applications for 2024 entry closed at 5pm on Friday 6 September. Applications for 2025 open on Monday 16 September.

More information

[email protected] +44 114 222 2646

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Celebrating the Milestone of Fusion Ignition

In 2022, Lawrence Livermore National Laboratory made history by demonstrating fusion ignition for the first time in a laboratory setting. Read about the people, facilities, capabilities and decades of tenacity that made this achievement possible.

Read about our fusion breakthrough

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Laser and experimental systems engineering graduate internship - summer 2025, company description.

Join us and make YOUR mark on the World!

Are you interested in joining some of the brightest talent in the world to strengthen the United States’ security? Come join Lawrence Livermore National Laboratory (LLNL) where our employees apply their expertise to create solutions for BIG ideas that make our world a better place.

We are looking for individuals that demonstrate an understanding of working in partnership with team peers, who engage, advocate, and contribute to building an inclusive culture, and provide expertise to solve challenging problems.

$6,410.00  - $7,780.00  Monthly for the 705.2 level

This position is under a step structure.  Please note that the step placement is determined by your most recent completed academic year.

Job Description

We have multiple openings for continuing graduate level scholars and recent graduates within one year to engage in practical research, design, and analysis experience to further their educational goals. You will provide technical and/or research support to projects in the areas of electrical engineering, mechanical engineering, optical engineering, computational engineering, or other related fields.  This support may include (but is not limited to) optics processing, design engineering, data mining and analysis, motion control systems, optomechanical systems, electromechanical systems and mechatronics, or a variety of diagnostic systems (including x-ray, optical, and neutron). These positions are in the Laser Systems Engineering & Operations Division in support of the National Ignition Facility & Photon Sciences Directorate.  These positions may be in Livermore or remote, depending on federal and local health and safety guidelines in the summer of 2025.

In this job, you will

• Provide technical and/or research, design, and/or analytical support to projects in the areas of electrical engineering, mechanical engineering, optical engineering, computational engineering, or other related fields, working with engineers, scientists, and technical staff members.
• Conduct research in assigned area under limited direction and supervision.
• Perform technical assignments of a basic degree of complexity and provide advanced technical support to scientist in scientific research and development projects.
• Gather and analyze data or information in support of scientific research.
• Attend relevant seminars and prepare a poster for the annual Summer Poster Symposium.
• Perform other duties as assigned.

Qualifications

• Must be a continuing college or university scholar in good standing at an accredited institution pursuing a graduate degree or a recent graduate within one year.
• Demonstrated academic achievement in a scientific curriculum.
• Experience applying advanced engineering or scientific principles to solve technical problems.
• Ability to apply basic engineering or scientific principles to solve technical problems.
• Communication skills necessary to communicate research project(s), document work and give a technical talk/presentation.
• Ability to present and communicate concepts and ideas.
• Effective interpersonal skills with the ability to work in a team environment.
• Experience working with personal computers and familiarity with Word, Excel, and PowerPoint.

Qualifications we desire

• GPA of 3.5 or above.

NOTE:  This is a Temporary Student Intern appointment.  This assignment is for a full-time position during the summer academic break; a co-op position, full-time during the academic semester/quarter, or a year-round part-time position during the academic year and full time during academic breaks. Refer to the Scholar Program website at https://scholars.llnl.gov/ for additional student employment information. 

Salaries are based on student academic level. 

Selected applicants will be required to provide transcripts.

Additional Information

All your information will be kept confidential according to EEO guidelines.

Why Lawrence Livermore National Laboratory?

• Included in 2024 Best Places to Work by Glassdoor!
• Holiday Pay
• Sick leave accrual
• Individual 401(k) contributions
• Inclusion, Diversity, Equity and Accountability (IDEA) - visit  https://www.llnl.gov/diversity
• Our core beliefs - visit  https://www.llnl.gov/diversity/our-values  
• Employee engagement - visit  https://www.llnl.gov/diversity/employee-engagement

Security Clearance

None required.  However, if your assignment is longer than 179 days cumulatively within a calendar year, you must go through the Personal Identity Verification process.  This process includes completing an online background investigation form and receiving approval of the background check.  (This process does not apply to foreign nationals.) 

Pre-Employment Drug Test

External applicant(s) selected for this position must pass a post-offer, pre-employment drug test. This includes testing for use of marijuana as Federal Law applies to us as a Federal Contractor.

Wireless and Medical Devices

Per the Department of Energy (DOE), Lawrence Livermore National Laboratory must meet certain restrictions with the use and/or possession of mobile devices in Limited Areas. Depending on your job duties, you may be required to work in a Limited Area where you are not permitted to have a personal and/or laboratory mobile device in your possession.  This includes, but not limited to cell phones, tablets, fitness devices, wireless headphones, and other Bluetooth/wireless enabled devices.  

If you use a medical device, which pairs with a mobile device, you must still follow the rules concerning the mobile device in individual sections within Limited Areas.  Sensitive Compartmented Information Facilities require separate approval. Hearing aids without wireless capabilities or wireless that has been disabled are allowed in Limited Areas, Secure Space and Transit/Buffer Space within buildings.

How to identify fake job advertisements

Please be aware of recruitment scams where people or entities are misusing the name of Lawrence Livermore National Laboratory (LLNL) to post fake job advertisements. LLNL never extends an offer without a personal interview and will never charge a fee for joining our company. All current job openings are displayed on the Career Page under “Find Your Job” of our website. If you have encountered a job posting or have been approached with a job offer that you suspect may be fraudulent, we strongly recommend you do not respond.

To learn more about recruitment scams:  https://www.llnl.gov/sites/www/files/2023-05/LLNL-Job-Fraud-Statement-Updated-4.26.23.pdf

Equal Employment Opportunity

We are an equal opportunity employer that is committed to providing all with a work environment free of discrimination and harassment. All qualified applicants will receive consideration for employment without regard to race, color, religion, marital status, national origin, ancestry, sex, sexual orientation, gender identity, disability, medical condition, pregnancy, protected veteran status, age, citizenship, or any other characteristic protected by applicable laws.

We invite you to review the Equal Employment Opportunity posters which include EEO is the Law and Pay Transparency Nondiscrimination Provision .

Reasonable Accommodation

Our goal is to create an accessible and inclusive experience for all candidates applying and interviewing at the Laboratory.  If you need a reasonable accommodation during the application or the recruiting process, please use our online form to submit a request. 

California Privacy Notice

The California Consumer Privacy Act (CCPA) grants privacy rights to all California residents. The law also entitles job applicants, employees, and non-employee workers to be notified of what personal information LLNL collects and for what purpose. The Employee Privacy Notice can be accessed here .

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Carnegie Mellon Institute for Strategy & Technology

Cmu's home for political science and international relations.

Master of Information Technology Strategy (MITS)

The Master of Information Technology Strategy is a cooperative endeavor administered by the Carnegie Mellon Institute for Strategy & Technology  and in partnership with the   College of Engineering  and the  School of Computer Science . This program creates leaders in the IT strategy space by allowing you to tailor your degree to an area of interest and teaching you how the puzzle pieces fit together -- both of which make you valuable to employers. The average starting salary for MITS graduates is nearly $120,000.

The program's two tracks provide flexibility, but their brevity -- the longer of the two takes sixteen months to complete -- is well-suited for those who want to quickly advance their professional career. Both tracks involve a required Capstone Project, in which teams of four to six students partner with a company, research center, or organization to help them solve a strategic problem.   

The program offers four areas of specialization: Data Analytics, Information Security, Technology Strategy & Governance, and Software and Networked Systems. No matter what you choose, you'll receive a blend of the other three, meaning you will leave Carnegie Mellon with a well-rounded skillset that makes you an attractive target on the job market. MITS is a STEM-designated degree according to the US Department of Homeland Security, meaning international students may apply for a longer period of Optional Practical Training. 

Graduates go on to careers as data scientists, software engineers, military cyber operations officers, artificial intelligence and machine learning engineers, and business technology analysts for companies such as Oracle, Microsoft, Barclays, Deloitte, Apple, Google, DoorDash, and Visa. 

For More Information

Please contact Mark Gardner , CMIST Graduate Program Manager.

Graduate Handbook

For graduate students entering fall 2024

For graduate students who entered fall 2023

The program has four areas of concentration:

• Data Analytics
• Technology Strategy & Governance
• Information Security
• Software and Networked Systems

The MITS program provides a multidisciplinary education that prepares students to define and conceptualize:

• the emerging environment of threats caused by cyber operations;
• opportunities for enhanced information analysis and exploitation;
• development and management of innovative information technology systems; and
• decision-making challenges associated with the above.

Study with the experts who are changing the game in their fields

When you take our Dynamic Network Analysis course, you'll be taking it with Dr. Kathleen Carley .  Dr. Carley specializes in network science, agent-based modeling, text-mining, and organizational and social theory framework.   In her work, she examines how cognitive, social, and institutional factors come together to impact individual, organizational, and societal outcomes. Sh e uses her expertise to address policy issues including counter-terrorism, human and narcotic trafficking, cyber and nuclear threats, organizational resilience and design, natural disaster preparedness, cyber threat in social media, and leadership.