Kaiqing Zhang

Kaiqing Zhang is an assistant professor in the Department of Electrical and Computer Engineering and the Institute for Systems Research. He is also an affiliate assistant professor in the Department of Computer Science and a member of both the Maryland Robotics Center and University of Maryland Center for Machine Learning.

Zhang’s research lies at the intersection of machine and reinforcement learning, game theory, and control theory, especially in multi-agent and safety-critical systems. His work has applications in intelligent and distributed cyber-physical systems, including robotics, smart grid and transportation systems.

Broadly speaking, the primary goal of his research is to lay theoretical foundations for the learning algorithms and systems that address data-driven sequential-decision-making problems in game theory and control theory, particularly in the presence of multiple decision-makers, toward large-scale and reliable autonomy.

Before joining UMD in 2022, he was a postdoctoral scholar at the Massachusetts Institute of Technology in the Laboratory for Information and Decision Systems and the Computer Science & Artificial Intelligence Laboratory. Zhang was also a Research Fellow at the Simons Institute at University of California, Berkeley.

He is the recipient of several awards and fellowships, including the Hong, McCully, and Allen Fellowship; the Simons-Berkeley Research Fellowship; a CSL Thesis Award; and the ICML Outstanding Paper.

Zhang received his doctorate in electrical and computer engineering and Coordinated Science Lab (CSL) from the University of Illinois at Urbana-Champaign in 2021.

Go here to view his academic publications on Google Scholar.