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  • 【SLAI Seminar】第十一期:AI for Mathematics: From Digitization to Intelligentization(Nov 16, 10:00)

【SLAI Seminar】第十一期:AI for Mathematics: From Digitization to Intelligentization(Nov 16, 10:00)

2025-11-16 论坛预告

We are delighted to announce that SLAI 11th Seminar will be discussing the topic on "AI for Mathematics: From Digitization to Intelligentization", from 10am, November 16th (Sunday) at B411 Lecture Hall.

 

About the Speaker: 

Professor Bin Dong is a Boya Distinguished Professor at the Beijing International Center for Mathematical Research, Peking University. He is also the Deputy Director of the Center for Machine Learning Research at Peking University, and the Executive Vice President of Zhongguancun Academy. Professor Dong completed his Bachelor of Science at Peking University in 2003, followed by a Master of Science from the National University of Singapore in 2005, and a Ph.D. from the University of California, Los Angeles, in 2009. His research interests lie in the areas of artificial intelligence, scientific computing and computational imaging. Professor Dong has been recognized for his contributions to these fields, including receiving the Qiu Shi Outstanding Young Scholar Award in 2014. He had the honor of delivering a 45-minute sectional lecture at the International Congress of Mathematicians (ICM) in 2022, and will deliver an invited lecture at the 11th International Congress on Industrial and Applied Mathematics (ICIAM) in 2027. He was selected for the New Cornerstone Investigator Program and received the Wang Xuan Outstanding Young Scholar Award in 2023.

 

Abstract:

Mathematical research has long faced bottlenecks that limit efficiency, and the introduction of artificial intelligence offers new opportunities to overcome these challenges. Against this backdrop, “AI for Mathematics” (AI4M) has emerged as a rapidly developing interdisciplinary field. This talk will begin by outlining the challenges and needs inherent to mathematical research, explaining why deep integration with AI is necessary. It will then review several representative advances in AI4M from recent years and compare the strengths and limitations of different technical approaches. Building on this, the talk will highlight the central role of formalization—the “digitalization” of mathematics—in substantially advancing AI’s reasoning capabilities. Finally, the talk will present the overall research plan of the Peking University AI4M team, share its interim achievements in formal model and tool design, automated reasoning systems, and benchmark construction, and conclude with an outlook on the future development of AI4M.

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