Research Focus: Deep Reinforcement Learning and Machine Learning for Energy Management Applications’, ‘Energy-Saving Control of Electric Vehicles’, ‘Powertrain Dyno validation of control strategies’
Industry Focus: Electrified Traction Systems;Automotive Electrification

Hao Wang received his B.Eng. and M.S. from the Beijing Institute of Technology, China, in 2019 and 2022, respectively. It was there that he won the National Scholarship for Undergraduate Students, the National Scholarship for Graduate Students, and the title of Beijing Outstanding Graduate. In September 2022, he joined the McMaster Automotive Resource Centre (MARC), Canada. He is currently pursuing his Ph.D. in mechanical engineering, under the supervision of Dr. Ali Emadi. His research interests include modelling and the control theory of electrified powertrains, deep reinforcement learning (DRL), and machine learning (ML) for energy management systems. 

Full Profile

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 and Dr. Amir Khajepour. 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, and bench 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). He has found the MARC testing facilities to be excellent, with a wonderful academic atmosphere. At McMaster University, he is pursuing his Ph.D., and his focus is on theoretical research and engineering applications for EVs. 

Hao’s current interests include modelling and the control theory of electrified powertrains. Additionally, he finds interest in DRL and ML theories for energy management systems.

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