Zheyuan Wang is a research engineer with a decade of experience applying machine learning to autonomous systems, currently building high-level driving automation at HAOMO.AI. He holds advanced degrees from Georgia Tech and Shanghai Jiao Tong University and completed a PhD focused on deep learning for human-robot coordination, multi-robot systems, and stochastic resource optimization. Over the past 7+ years he has specialized in graph neural networks for imitation and reinforcement learning, translating academic research into practical R&D. Based in Beijing’s Haidian District, he bridges rigorous theory and production needs, often tackling coordination challenges that require both learning-based policies and principled optimization. An understated strength is his sustained focus on multi-agent interaction dynamics—an area that informs his work on scalable, safety-aware autonomy.
10 years of coding experience
5 years of employment as a software developer
Doctor of Philosophy (Ph.D.), Electrical and Computer Engineering, Doctor of Philosophy (Ph.D.), Electrical and Computer Engineering at Georgia Institute of Technology
Master of Engineering (M.Eng.), Electronic and Communication Engineering, 2.45/3.3, Master of Engineering (M.Eng.), Electronic and Communication Engineering, 2.45/3.3 at Shanghai Jiao Tong University
Contributions:20 pushes, 1 branch in 2 years 3 months
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