DSI Research Scientist Matthew Feickert is an inaugural recipient of a URSSI fellowship for advancing research software development practices.
Year: 2025
DSI Special Seminar with Dr. Talitha Washington
Dr. Washington shared insights on advancing AI technology and policy responsible for ensuring these technologies promote innovation, accountability, and broad societal benefit.
Data Science for Earth Day
Earth Day, held each year on April 22, is a global event with local roots. Here are a few examples of data science research, tools, and learning opportunities at UW–Madison that help realize the vision of Earth Day.
Inaugural Open Award Recipients Recognized at the Research Bazaar
On March 20th, campus leaders were recognized at the UW–Madison Open Awards for their significant contributions to open scholarship and open source. Additionally, the ceremony recognized thirteen inaugural inductees into the Open Hall of Fame.
DSI Director and Staff Honored With Breakthrough Physics Prize
Kyle Cranmer, Alex Held, Matthew Feickert, Nils Krumnack, Garrett Merz, and Jay Sandesara were recognized for contributions to the CERN Large Hadron Collider.
Thank You, Research Bazaar Sponsors!
The Data Science Research Bazaar was a big success, and it would not have been possible without the support of our generous campus and industry sponsors.
UW–Madison Open Awards
Join us March 20, 9:30am, at the Data Science Research Bazaar as we recognize achievement in open source and open scholarship.
Solís-Lemus Recognized for Public Science Engagement
DSI Affiliate Claudia Solís-Lemus received the received the Bassam Z. Shakhashiri Public Science Engagement Award in recognition of her outreach and service.
Li Awarded Sloan Fellowship
DSI Affiliate Sharon Li is a 2025 Sloan Research Fellow. This award recognizes 126 of the most promising early-career scientists in the U.S. and Canada.
UW Research Partnership Yields First-of-its-Kind Soil Data Algorithm
University of Wisconsin professor of soil science Jingyi Huang and data scientist Maria Oros developed a new modeling tool for soil scientists. The pair used machine learning and public data to build the Soil Organic Carbon Assistant, which models changes in soil organic carbon.