PhD: Information Science

You belong here.

At CU, students are as important as the problems they solve.

Diverse Students

Information science is a broad discipline and our students come from a range of backgrounds. Some have computer science degrees and come prepared to take on information science with a toolkit of computational and data science methods. Some have little to no experience in computing but have backgrounds in social science or qualitative research. Some come to us with a rich knowledge of domains (e.g., public health, education or journalism) to which information science research and techniques can be applied. Some come straight out of undergraduate programs, others have already completed graduate degrees, and others have years of professional experience.

Our program is designed to help PhD students tailor their education towards their own research interests and skill sets while developing a shared body of knowledge around methods, computational techniques, theoretical frameworks and design practices.

Research a mile above ordinary.

High Impact Publications

Within the first few years of our PhD program, our students have published and presented work in venues such as CHI (human-computer interaction), VIS (information visualization), AAAI (artificial intelligence), CSCW (collaboration & social computing), NAACL (computational linguistics), Ubicomp (ubiquitous computing), AOIR (internet research), and SIGCSE (computer science education).

Examples of research groups led by our faculty include the VisuaLab, the Too Much Information (TMI) Lab, the Philanthropic Informatics Lab, the Creative Communities Group, That Recommender Systems Lab, and the Internet Rules Lab (IRL).

Learn more about the research interests of both our faculty and current PhD students on their profile pages.

Core Research Areas

Collaboration
Information Visualization
Data Science & Analytics
Ethics & Policy
Design and Human-Computer Interaction
Learning
Social Computing

Brianna Dym and Casey Fiesler. "Ethical and Privacy Considerations for Research Using Online Fandom Data." Transformative Works and Cultures, 2020.
Mikhaila Friske, Shanel Wu, and Laura Devendorf. “Entangling the Roles of Maker and Interpreter in Interpersonal Data Narratives: Explorations in Yarn and Sound.” Proceedings of the ACM SIGCHI Conference on Designing Interactive Systems (IDC), 2020.
Natalie Garrett, Nathan Beard, and Casey Fiesler. "More Than 'If Time Allows': The Role of Ethics in AI Education." Proceedings of the ACM Conference on AI, Ethics and Society (AIES), 2020.
Anthony T Pinter, Jacob M Paul, Jessie Smith, and Jed R Brubaker. "P4KxSpotify: A Dataset of Pitchfork Music Reviews and Spotify Musical Features." Proceedings of the AAAI International Conference on Web and Social Media (ICWSM).
Morgan Klaus Scheuerman, Jacob M. Paul, and Jed R. Brubaker. "How We’ve Taught Algorithms to See Identity: Constructing Race and Gender in Image Databases for Facial Analysis." Proc. ACM Human-Computer Interaction, CSCW, 2020.
Nasim Sonboli, Farzad Eskandanian, Robin Burke, Weiwen Liu, and Bamshad Mobasher. "Opportunistic Multi-aspect Fairness through Personalized Re-ranking." Proceedings of the ACM Conference on User Modeling, Adaptation and Personalization (UMAP), 2020.
Jordan Wirfs-Brock and Katie Quehl. "Giving Voice to Silent Data: Designing with Personal Music Listening History." Proceedings of the ACM Conference on Human Factors in Computing Systems (CHI), 2020.
Junnan Yu and Ricarose Roque. “Considering Parents in Coding Kit Design: Understanding Parents' Perspectives and Roles.” Proceedings of the ACM Conference on Human Factors in Computing Systems (CHI), 2020.

Across our department, there are many research projects happening at any given point, covering a wide range of domains and methods. Examples of funded projects in our department include research involving building computational tools to help scale qualitative data analysis, computer-mediated communication during crisis, organizational behavior in e-sports teams, research ethics for social computing, real-world machine learning, fairness-aware recommender systems, and humanizing algorithms.

Members of our faculty sometimes seek PhD prospective students with an interest in specific funded projects. Though applicants with any research interest are encouraged, here are some targeted recruitment calls:

Robin Burke is seeking students with research interests at the intersection of algorithmic fairness and recommender systems/personalization. Interest in computational social choice would be plus.
Laura Devendorf is seeking a PhD student who is interested in building design software tools in close collaboration with artists and engineers to join the Unstable Design Lab. This PhD project is funded by a National Science Foundation CAREER grant entitled "Developing Next-Generation Rapid Prototyping Tools to Catalyze Innovation in Smart Textiles." Much of the work in the Unstable Design Lab explores smart textiles as a context within which to explore equity in innovation, particularly between people who identify as craftspeople or technologists. Students in the lab are artists and technologies and produce open-source software tools as well as publications and artworks that take a critical perspective on design and design futures. For more information, please see our lab website.
Casey Fiesler is seeking students interested broadly in technology ethics and/or online communities, including ethics education in computing, data privacy and ethics, and online support for marginalized and vulnerable groups.
Bryan Semaan is seeking students interested broadly in the intersection between resilience, marginalized identities, and technology. He is seeking students who wish to draw on critical race, feminist, and postcolonial perspectives to advance explorations of how people with marginalized racial and ethnic identities are working to appropriate and create sociotechnical systems for their own uses, how existing sociotechnical systems are exacerbating or creating new sources of marginalization, and how we can work to create more just, equitable, and fair technology. Students could explore these phenomena in myriad contexts or by looking at diverse populations, such as through explorations of algorithmic systems like TikTok, moderated online community spaces like Reddit and Twitch, people's experiences undergoing transitions, and more. For more information, please see our lab website.
Amy Voida is seeking students interested in conducting empirical or design research about the role of information and communication technologies in supporting nonprofit or other philanthropic work.

Student Voices: Fellowships & Industry Research Internships

Aaron Jiang (Facebook)

"My research internship at Facebook really let me see what it’s like to do industry research and work on projects that can impact billions of people and has led to ongoing collaborations. My understanding of industry research from the internship will also help me with industry job interviews."

Jessie Smith (Microsoft Research)

"During my internship with Microsoft Research I was able to collaborate with the inspiring scholars that got me interested in doing research in the first place and I came out of the summer with a project and a publication on the way! This experience helped me gain a better understanding of the difference between doing research in academia and industry and has given me good insight into the kind of job I hope to get at the end of my degree."

Jordan Wirfs-Brock (Yahoo!)

"During my internship with Yahoo, I got intense hands-on experience with many research methods that I wouldn't have necessarily had the chance to use during the academic year. Experiencing research at the pace of industry expanded my understanding of how to scope my own projects."

Morgan Klaus Scheuerman (Microsoft)

"I am beyond honored to receive the Microsoft PhD Fellowship this year. Out of the thousands of applicants, Microsoft decided that my research on identity in AI was impactful and important enough to fund for the next two years. I'm super excited to get to focus fully on my dissertation work for the rest of my PhD career."

PhD Requirements

Application Deadlines

US applicants:
Dec. 1

International applicants:
Dec. 1

How to Apply

The PhD in Information Science is for students who want to engage in empirical investigations of interdisciplinary problems. Students in the PhD program will learn a diversity of methods, theoretical frameworks, design practices and computational techniques. A PhD student's scholarly practice will include collaborative research on grant-driven projects.

The scholarly skills required of PhDs in information science are fundamentally analytical, creative, interdisciplinary and in constant interaction with information that is generated, manipulated and transformed within and across domains. The PhD aligns culturally with the grant-driven, collaborative “lab model” of research that characterizes the natural and engineering sciences, but is nevertheless deeply integrative of the social sciences and humanities in its scholarly pursuit and intellectual contributions.

The PhD program in information science requires a minimum of 30 course credit hours and 30 thesis credit hours. Students are encouraged to take courses outside of the department beyond any departmental foundation courses pending approval by their advisor and the graduate committee. After a written and oral preliminary exam, students go on to specialize in a dissertation area in consultation with their committees. Completion of the PhD will take approximately five years.

See INFO PhD program handbook for more information.

Admissions Requirements
Contact Graduate Advising

Bachelor’s degree or its equivalent
We encourage applications from individuals representing the broad range of disciplines that bring fundamental skills and insights to bear on the range of issues related to understanding and shaping a future of information science as envisioned above. However, all students admitted to the program will be expected to develop a breadth of competencies (including empirical, computational and designerly competencies) that are essential to being a researcher in this diverse, interdisciplinary field. One’s ability and willingness to expand skillsets should be demonstrated in the statement of purpose.
CV or resume
Statement of purpose (maximum of two pages):
- Your statement of purpose should describe a question, problem or topic in information science that you have a passion to address.
- Please describe how your previous academic training, professional experience and/or personal passions have led you to this question, problem or topic and have drawn you to this degree program.
- Identify the faculty members with whom you would be interested in working and why.
Undergraduate GPA of at least 3.20, and graduate GPA of 3.50 if any prior graduate coursework was taken.
One unofficial transcript from each college or university attended.
Three letters of recommendation from people qualified to judge your potential for success in graduate school.
- The most compelling letters will provide specific observations about the candidate’s promise in analytical thinking, scientific communication (both oral and written), research and teaching, as well as a demonstration of teamwork and collegiality.
GRE scores are not required for students applying to our graduate program. Applicants are welcome to submit a general GRE score but will not be at a disadvantage if they choose not to.
Optional: A writing sample in addition to the statement of purpose.
International applicants must also have a TOEFL score of 75 or an IELTS score of 6.0.

Phone: 303-492-7977

Email: cmcigrad@colorado.edu

PhD: Information Science

In this section: Information Science

Diverse Students