Hao Wang received his B.Eng. and M.S. from the Beijing Institute of Technology in 2019 and 2022. During his studies, he earned several top honours, including the National Scholarship for Undergraduate Students, the National Scholarship for Graduate Students, and recognition as a Beijing Outstanding Graduate. He joined the McMaster Automotive Resource Centre (MARC) in September 2022 and is now pursuing a Ph.D. in mechanical engineering under the supervision of Dr. Ali Emadi. His research focuses on modelling and control of electrified powertrains, as well as applying deep reinforcement learning and machine learning to energy management systems.
Full Profile
Hao Wang’s interest in natural sciences and engineering technology brought him to the Beijing Institute of Technology (BIT) in 2015. During his undergraduate studies, he built a strong foundation in advanced mathematics, mechanical design, 3D modeling, theoretical mechanics, automotive theory, electric vehicle configuration, and control theory. He consistently ranked near the top of his class. Competitions such as the Structural Design Challenge strengthened his teamwork skills and work ethic. In 2019, he earned the National Scholarship for Undergraduate Students and the Beijing Outstanding Undergraduate Student award.
After earning his bachelor’s degree, Hao entered the master’s program at BIT without an entrance exam. He joined the National Engineering Laboratory for Electric Vehicles and worked under Dr. Hongwen He and Dr. Amir Khajepour. He contributed to national R&D projects and gained experience in vehicle modeling, software simulation, and hardware-in-the-loop testing. During this period, he also discovered machine learning and reinforcement learning, which sparked his interest in intelligent control.
Regular discussions with his supervisors and peers helped him deepen his understanding of artificial intelligence. He explored practical ways to apply theoretical algorithms to engineering problems. He used model predictive control and deep reinforcement learning to improve energy-efficient control strategies for electric vehicles. His research produced two international journal publications. He also received the National Scholarship for Graduate Students and the Beijing Outstanding Graduate Student award.
In September 2022, Hao joined Dr. Ali Emadi’s group at the McMaster Automotive Resource Centre (MARC). He is now pursuing a Ph.D. in mechanical engineering. His research focuses on modeling and control of electrified powertrains, as well as using deep reinforcement learning and machine learning to develop advanced energy-management systems for electric vehicles.
