About

Zheng Wen is a highly accomplished Research Scientist specializing in Reinforcement Learning and Dynamic Optimization. With almost a decade of relevant experience, he is currently serving as a Research Scientist at DeepMind, where he is involved in cutting-edge research. Additionally, he is an Adjunct Lecturer at Stanford University, where he teaches a PhD-level course on Dynamic Programming and Stochastic Control. Prior to his current roles, Zheng Wen served as a Research Scientist at Adobe Research and Yahoo Labs, where he made significant contributions to the field. He holds a Ph.D. in Electrical Engineering from Stanford University, where he worked under the guidance of Prof. Benjamin Van Roy. He also holds a Ph.D. minor in Business/Finance from Stanford Graduate School of Business, which has further enhanced his expertise. Zheng Wen began his academic journey with a Bachelor of Engineering in Electrical Engineering and Automation from Harbin Institute of Technology, followed by a Master of Science in Electrical Engineering and Computer Science from Washington State University. He also spent a semester as an Undergraduate Exchange Student at The Hong Kong University of Science and Technology, where he studied Electrical Engineering and Computer Science. Zheng Wen is a member of several prestigious organizations, including ACM, INFORMS, and IEEE. He has a strong TechStack, including expertise in research and reinforcement learning. His personal homepage is a testament to his dedication and passion for his work. Zheng Wen's extensive experience, coupled with his academic achievements and research contributions, makes him a valuable asset to any organization. His passion for learning and sharing knowledge makes him an ideal mentor and teacher.