- Computational Social Science
- Critical Data Studies
- Data Science
- Economics and Information
- Education Technology
- Ethics, Law and Policy
- Human-Computer Interaction
- Human-Robot Interaction
- Incentives and Computation
- Infrastructure Studies
- Interface Design and Ubiquitous Computing
- Natural Language Processing
- Network Science
- Social Computing and Computer-supported Cooperative Work
- Technology and Equity
Below are the requirements for completing a PhD in Information Science at Cornell. If you have any further questions please contact our Graduate Program Coordinator, Barbara Woske, via email or phone, 607-254-5347.
Required Core Courses
All IS doctoral students are required to complete 4 of the following 5 core courses, in consultation with your advisor, with grades of B+ or better.
INFO 6010: Computational Methods for Information Science Research
Computation is an essential tool for many facets of information science research. Examples of its utility include capture, access and analysis of digital data; visualization of that data for analysis, interpretation and information extraction; construction of user focused applications; and analysis of textual and sensor-derived information to detect patterns and dynamics of human activities, social interactions and social networks. Effective use of computation requires a mixture of skills including structuring data, accessing data, programming, choosing and applying computational analysis methods, and designing visualizations. This course covers the mixture of these skills, with the goal of providing information science graduate students with the appreciation of their utility and the ability to employ them in future research. The course is project-based, allowing students to understand the use of computational methods for their individual research interests. Prerequisites: programming ability at the level of CS1110 or CS1112 or INFO1100. This includes variables, arrays, strings, loops, conditionals, methods and functions, basic recursion, file IO, object orientated design, debugging. No prior knowledge of Python is required.
INFO 6210: Information, Technology, and Society
This course addresses the broader contextual issues that influence and control the dissemination of, control of, access to, and development of information in society and culture. Students will explore how technology depends not just on designers and technologists, but also on regulations, institutions, user appropriation, and other social and cultural forces. We will analyze the social and societal implications of technologies and design decisions, and develop facility with taking sociocultural issues into account in research, technology design, and policy development. Course topics include histories of information, the social life of information, consequences of information infrastructure, information policy, and values in design. In exploring these topics, students will develop a conceptual understanding of qualitative methods and the ability to deploy one of these methods (e.g., ethnography, interviews, historical analysis) at a basic level.
INFO 6260: Networks, Crowds, and Markets: Foundations for Formal Analysis and Design
Information Science studies systems at the juncture of people and technologies – their behavior, analysis and design. This doctoral level mixed lecture-seminar course is an introduction to the formal analysis of social systems: we will introduce concepts from mathematics, computer science and economics that are fundamental to analyzing many settings – networks, crowds, markets – studied by information science, and see how formal reasoning using abstract mathematical models can help analyze and predict outcomes. Throughout, we will draw on real-world examples such as social networks, Internet markets, and crowd-sourcing to illustrate how formal analysis can inform the understanding and design of social systems.
INFO 6310: Behavior and Information Technology
This course explores the behavioral foundations of communication technology and the information sciences, and the ways in which theories and methods from the behavioral sciences play a role in understanding people’s use of, access to and interactions with information and communication technologies. Multiple levels of analysis -- individual, small group, and larger collectives -- will be included, along with multiple disciplinary perspectives. Course topics will include: cognitive perspectives on design, attention and memory; psychological theories of language use and self-presentation in computer-mediated communication; social psychological perspectives on coordination and group work; and organizational science theories of social ties and relationships. Methodological topics will include the design of lab and field experiments, survey studies, and field observations, common statistical techniques used in the behavioral sciences and how to interpret them, and strategies for reporting results from behavioral science studies.
INFO 6520: Design Core // INFO 6940 SEM 301T
Please note: this course has two different course numbers – one for the Ithaca campus, and another for the Tech campus. The course number for Ithaca-based students is INFO 6520, while for NYC-based students at the Tech campus, the course number is INFO 6940 SEM 301T.
This class will provide a hands-on approach to teach students how to produce innovative solutions to complex design problems covering engineering, experimental design, and fabrication among others. The class will be taught in a studio format. Teaching will take place in a dedicated teaching space with extensive interactions with the teaching staff.
Each Ph.D student is required to serve as a teaching assistant for two semesters.
Information Systems examines the computer science problems of representing, organizing, storing, manipulating, and using digital information.
Human Computer Interaction uses an interactive, user-centered design approach to study the interplay between technology and what people do with technology.
Cognition focuses on the human mind, which is the ultimate producer and user of information.
Social Aspects of Information studies the cultural, economic, historical, legal, political, and social contexts in which digital information is a major factor.
Each Ph.D. student will select an external minor. This will often be a closely related field, such as Cognitive Studies, Communication, Computer Science, Science & Technology Studies, Economics, Linguistics, Mathematics, Operations Research, Psychology, or Sociology.
Forming a Committee
Each student's committee must consist of three members representing each of the following: primary IS concentration (this is the committee chair), secondary IS concentration, and external minor. The committee must be formed no later than the end of the third semester. (See Cornell's Graduate School page on Choosing Your Committee.) Each PhD student's campus location is determined by the location of their preferred or temporary advisor. Students should consider this when choosing their permanent advisor, since students are expected to be on the same campus – either Ithaca or New York City – as their advisors.
The student's committee may require the student to take courses in addition to the core requirements.
The A exam tests the student's breadth in Information Science and depth in their proposed thesis area. The committee has to be selected before the A exam can take place. Students generally take the A exam after completing their coursework and at a point where they've outlined their research and have some preliminary results. They write responses to questions posed by their committee members, and then discuss their answers at an oral examination with their full committee present.
Students are expected to make a thesis proposal by the end of their third year. As part of the thesis proposal, the student will be required to demonstrate depth in at least one concentration, sufficient to carry out fundamental research. The student's Ph.D. committee will decide how this expertise will be evaluated.