Wanli Cheng

Wanli Cheng is a PhD candidate in the Faculty of Computing and Data Sciences at Boston University. Previously he received a B.A. in Pure and Applied Math from Boston University and a M.S. in Physical Sciences from the University of Chicago, where he had extensively studied probability, statistical physics and information theory. 

Wanli is interested in AI4Science in general, and in particular, he is interested in applying geometric deep learning (GDL) methods in quantum chemistry and molecular biology. He is also interested in theoretical research of GDL including graph neural networks (GNN), group equivariant generative models and other related topics. Wanli also enjoys learning about other possible AI applications (e.g., multimodal learning, large language models) in sciences.