Abstract: This presentation delves into the recent advancements in applying artificial intelligence (AI) to mathematical exploration. Initially, we will outline the current state of integrating AI methodologies, including machine learning, deep learning, and neural networks, into mathematical research, thereby fostering enhanced approaches and innovative concepts. Subsequently, we will highlight some preliminary results from ongoing research in this intersecting domain. Concluding the discussion, we will anticipate the future trajectory of research at the intersection of AI and mathematics, focusing on the potential of AI techniques to tackle new challenges and uncover novel problems in mathematical studies.
Bio: Bin Dong is a professor of the Beijing International Center for Mathematical Research, Peking University. He is the assocaite director of the Center for Machine Learning Research at Peking University, and an affiliated faculty member of the National Biomedical I maging Center. He is also a New Cornerstone Investigator. He received his B.S. from Peking University in 2003, M.Sc from the National University of Singapore in 2005, and Ph.D. from the University of California Los Angeles in 2009. Bin Dong's research interest is in the mathematical analysis, modeling, and computations in computational imaging, scientific computing, and machine learning. He currently serves the editorial board of I nverse Problems and Imaging, CSIAM Transactions on Applied Mathematics, Journal of Computational Mathematics and Journal of Machine Learning. He received the Qiu Shi Outstanding Young Scholar Award in 2014 and was invited to deliver a 45-minute sectional lecture at the International Congress of Mathematicians (ICM) 2022.