Wenshuo Wang received his Ph.D. degree in Mechanical Engineering from Beijing Institute of Technology (BIT). Beijing, China in 2018. He is now working as a Postdoctoral Researcher at McGill University, supported by IVADO Postdoc Fellowship Awards. Before joint McGill, he also worked as a Postdoc at the University of California, Berkeley (2019-2020) and Carnegie Mellon University (2018-2019). During his Ph.D. program, he also studied as a student research scholar at UC Berkeley (2015-2017) and the University of Michigan Transportation Research Institute (UMTRI) (2017-2018). He obtains the IVADO Postdoc Fellowship Awards in Canada (2020), a member of the 3rd Summer School on Cognitive Robotics (2019), the Best Ph.D. Dissertation Awards in China Society of Automotive Engineers (SAE-China) (2018), the Excellent Ph.D. Programs Fellowship of BIT (2017). Now he serves as the Associate Editor for IEEE Transactions on Vehicular Technology (2021 --), Transportation Safety and Environment (2021 --), and IET The Journal of Engineering (2020 --). He serves as the technical program committee of the 2021 International Conference on Intelligent Control and Automation Engineering (ICAE 2021) and the Autonomous Vehicle Vision 2021 (AVVision’21). He also serves as the chair & co-chair of 3rd AVVision Workshop on CVPR (2020) and the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS’21), Session on ‘Cognitive Urban Autonomous Driving’ for the IFAC Conference on Cyber-Physical & Human Systems (2020), Workshop on ‘Decision-making and control on driver-automation interaction’ for IEEE IVs (2018). His research focuses on Bayesian learning, reinforcement learning, and data science, and associated applications to human driver behavior, multi-agent interaction, autonomous vehicles, and intelligent transportation systems in common-but-challenging traffic scenes, in which he has contributed over 50 papers in international journals and conferences.

Research Interests

• Human behavior modeling and prediction, Cognition & perception, Human-robot interaction, Data science
• Intelligent transportation, Autonomous driving, Multi-agent interaction, Advanced driver assistance systems
• Bayesian statistics & machine learning, Stochastic processes, (Inverse) reinforcement learning and optimal control