Study Data Science
Data Science is one of the fastest growing majors at UW-Madison. Whether you are interested in a data science career, course, or workshop, opportunities abound here! Learn about undergraduate majors, graduate programs, the data science certificate, workshops, and internships and careers.
Explore Campus Resources
Data science has applications in all disciplines, and Data Science @ UW is your connection to data science institutes, centers, and programs across the UW-Madison campus. It’s also the place to find research funding and resources, coding meetups, seminars and events, data science faculty and communities of practice, student organizations, and more!
Collaborate With Us
Data science innovation at UW-Madison furthers the Wisconsin Idea by fueling discovery and economic development in all corners of the state and beyond. We are committed to fostering an inclusive culture in data science. Campus, industry, and community partners can benefit from our data science services.
Data Science Events
- June
- June 19
- June 25Exploring AI in Teaching: Summer Reading SessionsCenter for Teaching, Learning & Mentoring12:00 PM, Online
- June 27"AI and Society: Community Impacts and New Directions"Interactive Two-Day Workshop for Educators, Community Organizations, and Local BusinessesAll day, Concourse Hotel, Madison, WI
News and Announcements
CDIS and DSI Moving to Morgridge Hall This Summer
Morgridge Hall construction will conclude this summer, with classes expected to start in the fall. The new facility will house the School of Computer, Data, & Information Sciences along with the Data Science Institute, Center for High Throughput Computing, and biostatistics and medical informatics department.
Ilias Diakonikolas Wins ACM Grace Hopper Award for Breakthrough Techniques in Algorithm Design
Diakonikolas, Sheldon B. Lubar professor of Computer Sciences, received the 2024 Association for Computing Machinery (ACM) Grace Murray Hopper Award, one of the highest honors for young researchers in computing.
Data Science Hub Shares Progress in 2024 Impact Report
In 2024, the Data Science Hub continued to support researchers in learning data science and computing skills and applying those skills to their research. Read their 2024 Impact Report to see how they are empowering data-rich research.
Grace Wahba Awarded the International Prize in Statistics
This award recognizes Wahba's groundbreaking work on smoothing splines, which has transformed modern data analysis and machine learning. Wahba joined the University of Wisconsin-Madison in 1967 as the first female faculty member in the department of statistics.
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Faces of Data Science
“It’s easy to fall into the trap of producing new ideas and new computational methods that get further disconnected form the real needs of domain scientists. We always try to stay connected to the domain scientists and work with the many great people right here on this campus who are working on the early stages of drug discovery.”
Anthony Gitter
Associate Professor, Department of Biostatistics and Medical Informatics; Jeanne M. Rowe Chair, Morgridge Institute for Research
Anthony Gitter grew up in Wisconsin, but that wasn’t the main reason he returned to his home state for a joint faculty appointment at UW–Madison and the Morgridge Institute. As a computational biologist, he is motivated to do collaborative, intellectually stimulating work that benefits society while advancing frontiers of knowledge. This unique faculty position offered him the opportunity to “be the researcher I wanted to be.”
Gitter designs novel computational methods to study diseases, particularly viral infections and cancer, and develop new drugs and proteins. A core problem in biology is understanding how cells respond to changes. Gitter’s team creates algorithms to trace messages passed between networks of biomolecules within cells; for example, to understand what happens when human cells are infected with viruses. His lab also develops machine learning models to dramatically speed up the process of drug discovery, collaborating with domain scientists to target the most promising chemicals for lab experiments.
Open science and open source are part of the Gitter Lab’s culture, and his team openly shares the data, code, and software they’ve developed. To build trust in AI and machine learning, Gitter believes that open, transparent practices are critically important.