Accelerating Scientific Discovery and Nanoporous Material Design via Interpretable Machine Learning 

Dr. Guorong Weng received his Ph.D. in Chemistry in 2023 from the University of California, Santa Barbara, where he conducted research on stochastic electronic-structure theory under the supervision of Vojtech Vlcek. From 2023 to 2025, he carried out postdoctoral research in the Alexandrova group at the University of California, Los Angeles, focusing on theoretical simulations of topological materials for catalytic applications. In January 2026, Dr. Weng joined Macau University of Science and Technology as an Assistant Professor. His research group develops advanced computational methods that integrate artificial intelligence, data-driven techniques, and electronic-structure theory to address challenging problems in chemistry and materials science. Dr. Weng currently serves as a junior editor for AI Agent and is an active peer reviewer for this and other leading journals in the field.

Yuan Gao is an Associate Professor at Kyushu University, Japan. He received his Ph.D. from the University of Tokyo, M.Eng. from Tongji University, and B.Eng. from Xi’an University of Architecture and Technology. His research focuses on interpretable deep learning for energy forecasting, model predictive control under uncertainty, and reinforcement learning for the operation and optimization of building energy systems. He has published more than 30 papers in these areas, including multiple ESI Highly Cited Papers.