Explore the mathematical foundations of learning and artificial intelligence through a workshop designed to make rigorous theory accessible to a broader research community.
Featuring perspectives on how concepts like “learning” and “intelligence” can be formally defined and studied, the program highlights the rich problems, structures, and connections shaping this field. Designed for mathematically-inclined researchers, this workshop welcomes participants who are curious about theoretical machine learning and AI, whether new to the area or looking to deepen their understanding.
This event is part of the Frontiers in Data Science and AI initiative at the Data Science Institute, Columbia University.
REGISTER
REGISTRATION DEADLINE: The Columbia Morningside campus is open to the Columbia community. If you do not have an active CUID, the deadline to register is at 12:00 PM the day before the event.
Speakers:
- DSI Frontiers Awardee: Daniel Hsu: Associate Professor of Computer Science, Columbia Engineering
- Christos H. Papadimitriou: Donovan Family Professor of Computer Science; Provost’s Senior Faculty Teaching Scholar, Columbia Engineering
- Elisenda Grigsby: Professor, Math Department, Boston College
- Toniann Pitassi: Jeffrey L. and Brenda Bleustein Professor of Engineering, Columbia Engineering
- Joan Bruna Estrach: Professor of Computer Science, Data Science, and Mathematics, Courant Institute, New York University
- Kriste Krstovski: Associate Research Scientist, Data Science Institute
Contact Information
Data Science Institute
[email protected]