ZHANG, Jiheng

Jiheng Zhang is a professor at the University of California, Berkeley, specializing in operations research, applied probability, and stochastic systems. His research focuses on the analysis and optimization of queueing systems, stochastic networks, and their applications in various domains such as telecommunications, healthcare, and logistics. He has made significant contributions to the understanding of diffusion approximations, heavy-traffic limits, and the performance analysis of large-scale service systems. Zhang has also worked on problems related to resource allocation, staffing, and control in service operations. His work has been widely published in top-tier journals and conferences, and he has received numerous awards for his research and teaching.

Jiheng Zhang is a researcher at The Hong Kong University of Science and Technology, specializing in Applied Probability, Stochastic Modeling and Optimization, and Numerical Methods and Algorithm. His work focuses on the analysis and optimization of queueing systems, with applications in logistics, ride-sharing, and customer service. Zhang's research explores fluid and diffusion limits of many-server queues, dynamic scheduling policies, and staffing strategies for service systems with impatient customers. He also investigates reinforcement learning, bandit problems, and differential privacy in decision-making under uncertainty. His publications highlight the intersection of stochastic processes, operations research, and algorithm design for real-world systems.