Qi Zhang selected as first recipient of David J. Kuck Dissertation Prize

His work is in the area of coordinating systems of autonomous agents that operate in uncertain, dynamic environments.

Qi Zhang Enlarge
CSE PhD alumnus Qi Zhang.

CSE alumnus Qi Zhang has been selected as the first recipient of the David J. Kuck Dissertation Prize. Established in 2020 by EECS alumnus David J. Kuck, the annual award recognizes the most impactful PhD dissertation submitted by a student in the University of Michigan’s program in Computer Science and Engineering.

Zhang graduated from the CSE PhD program in August 2020. His dissertation was entitled, “Making and Keeping Probabilistic Commitments for Trustworthy Multiagent Coordination.” He was co-advised by Toyota Professor of Artificial Intelligence Satinder Singh Baveja and Professor Edmund Durfee.

In his dissertation abstract, Zhang addresses the issue that in a large number of real world domains, such as the control of autonomous vehicles, team sports, medical diagnosis and treatment, and many others, multiple autonomous agents need to take actions based on local observations, and are interdependent in the sense that they rely on each other to accomplish tasks. Because of this interdependency, achieving desired outcomes in these situations requires interagent coordination. The form of coordination his thesis focuses on is commitments, where an agent, referred to as the commitment provider, specifies guarantees about its behavior to another, referred to as the commitment recipient, so that the recipient can plan and execute accordingly without taking into account the details of the provider’s behavior.

Zhang is now an Assistant Professor in the Computer Science and Engineering Department at the University of South Carolina, where his research seeks solutions for coordinating systems of decision-making agents operating in uncertain, dynamic environments. He employs ideas from planning and reinforcement learning to develop and analyze algorithms that autonomously coordinate agents in an effective, trustworthy, and communication-efficient manner.