Abstract:

This presentation delves into the recent advancements in utilizing artificial intelligence (AI) within the realm of mathematical exploration. Initially, we will outline the history and 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.

Biography: 

Professor Bin Dong 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 (UCLA) in 2009. Then he spent 2 years in the University of California San Diego (UCSD) as a visiting assistant professor. He was a tenure-track assistant professor at the University of Arizona since 2011 and joined Peking University as an associate professor in 2014. He is currently a professor at the Beijing International Center for Mathematical Research and the deputy director at the Center for Machine Learning Research, Peking University. His research interest is in computational imaging, scientific computing and machine learning.