Hao Wang received his B.Eng. and M.S. degrees from the Beijing Institute of Technology, China, in 2019 and 2022, respectively. In September 2022, he joined the McMaster Automotive Resource Centre (MARC) in Canada, where he is currently pursuing a Ph.D. in Mechanical Engineering under the supervision of Dr. Ali Emadi. His research interests include modeling and control of electrified powertrains, as well as the application of deep reinforcement learning (DRL) and machine learning (ML) to energy management systems.
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Having an avid interest in the natural sciences and engineering technology, Hao was admitted to the Beijing Institute of Technology (BIT), China, in 2015. During his undergraduate studies, Hao built a solid foundation in advanced mathematics, mechanical design, 3D modelling, theoretical mechanics, automotive theory, electric vehicle configuration, and control theory.
For four years, he was consistently ranked among the top of his class, in academic performance. Through participation in technology competitions, like the structural design competition, he developed a spirit of teamwork and a responsible work ethic. His outstanding performance earned him the National Scholarship for Undergraduate students. He also received the Beijing Outstanding Undergraduate Student award, in 2019.
After obtaining his bachelor’s degree, Hao was admitted as a master’s student to BIT, without an entrance examination. He joined the National Engineering Laboratory for Electric Vehicles and continued his research on the modelling and control of electrified powertrains, under the supervision of Dr. Hongwen He. At this stage, he participated in several key national R&D projects in China, accumulating valuable experience in electric vehicle modelling, software simulation, hardware-in-loop testing. Moreover, this was where he received his initial exposure to ML and RL theory.
Through actively communicating with his supervisor and the excellent students in the research group, Hao deepened his understanding of artificial intelligence (AI) theory. Integrating engineering problems with theoretical knowledge, he applied the model predictive control (MPC) method and DRL algorithms to achieve energy-efficient control for electric vehicles (EVs). He even published two papers in international journals. Again, Hao received the National Scholarship for Graduate Students. Not only that, but he also earned the Beijing Outstanding Graduate Student award, for a second time.
In September 2022, Hao joined Dr. Ali Emadi’s research team at the McMaster Automotive Resource Centre (MARC), where he is pursuing his Ph.D. at McMaster University. His research focuses on both theoretical and applied aspects of electric vehicle (EV) technology. His current interests include modeling and control theory of electrified powertrains, as well as the application of deep reinforcement learning (DRL) and machine learning (ML) for efficient, effective, and safe energy management systems.
