主讲人：马玮 助理教授

邀请人：孙剑教授、秦国阳博士

时间：2023年9月22日（周五）上午9:00-11:00

地点：tyc8722太阳集团城（通达馆）103会议室

主讲人简介：

Dr. Ma Wei is currently an assistant professor with the Department of Civil and Environmental Engineering at the Hong Kong Polytechnic University (PolyU). He received bachelor’s degrees in civil engineering and mathematics from Tsinghua University, China, master’s degrees in Machine Learning and Civil and Environmental Engineering, and Ph.D. in Civil and Environmental Engineering from Carnegie Mellon University, USA. Dr. Ma’s research focuses on the intersection of AI and transportation modeling, with applications for smart and sustainable mobility systems. He currently directs the PolyU Mobility AI Lab (http://polyu-mobility-ai-lab.com/), and his research has been supported by various agencies, such as Research Grants Council of Hong Kong, Transport Department in Hong Kong, National Natural Science Foundation of China, and Uber. Dr. Ma received the best paper award (theoretical track) at INFORMS Data Mining and Decision Analytics Workshop and Kikuchi-Karlaftis Best Paper Award by the Transportation Research Board (TRB).

主讲内容简介：

With the rapid development of emerging communication technologies (e.g., mobile internet), sensing technologies (e.g., cameras), and mobility services (e.g., personalized mapping services), transportation systems have become unprecedentedly complicated and inter-connected for many metropolitan areas like Hong Kong over the past decade. The drastic changes have created opportunities and challenges for better transportation modeling and management frameworks. In this talk, Dr. Ma will introduce his Mobility AI lab's efforts in building a holistic framework for operating and managing the urban transport system, which aims to sense, learn, model, and manage the complicated transportation system by integrating engineering and Artificial Intelligence (AI) models. Topics will cover advanced sensing technologies, transfer learning across cities, meso-macro dynamic traffic simulation, and reinforcement learning for traffic control.

欢迎各位老师、同学参加院级高等讲堂！

tyc8722太阳集团城研究生会
tyc8722太阳集团城青年教师沙龙