OpenAI is collaborating with UCLA’s Institute for Pure and Applied Mathematics (IPAM) on a full-day convening of leading mathematicians, theoretical physicists, and AI researchers to explore how frontier reasoning models are beginning to accelerate discovery in highly abstract scientific domains. Through a sequence of focused lectures, disciplinary deep dives, and panel discussions, the program will highlight innovative applications of AI in mathematics and physics and offer researchers a front-row view of an emerging era in which AI acts as an accelerant for solving the hardest scientific problems. Mid-event, a fireside conversation between Terence Tao and Mark Chen will reflect on the past year of advancements in reasoning models and explore how AI is reshaping mathematical inquiry.
This year’s program builds upon last year’s widely viewed Tao–Chen discussion, which introduced the idea of AI as a “universal translator” capable of enabling researchers to meaningfully collaborate outside their own domains. This convening aims to bring that vision closer by educating, inspiring, and forging connections among researchers in service of accelerating scientific discovery. The day will culminate in the Bhaumik Public Lecture, delivered by Kevin Weil, who will share OpenAI for Science’s roadmap and ambitions to compress decades of scientific insight into years and expand what becomes possible when advanced AI systems meet human creativity.
This event is organized jointly by IPAM, the UCLA Department of Physics and Astronomy, OpenAI and Bhaumik Institute.
Zvi Bern (University of California, Los Angeles (UCLA))
Dima Shlyakhtenko (Institute for Pure and Applied Mathematics, UCLA)
Terence Tao (University of California, Los Angeles (UCLA))
Open AI Forum
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