Qun Li

Qun Li is a Professor of Computer Science at the College of William and Mary, leading the Edge Computing Laboratory. He holds an IEEE Fellow distinction and has served as Graduate Director (2010-2011). His research focuses on edge computing, operating systems, distributed systems, and security & privacy, with over 100 publications in top venues like ACM CCS, ICSE, and NSDI. Li has advised numerous PhD students, including Zhengrui Qin and Ed Novak, who now hold academic positions. He chairs conferences including ACM/IEEE Symposium on Edge Computing (SEC'22) and has editorial roles at IEEE Internet Computing and Transactions on Computers. Key awards include an NSF Career Award. His work emphasizes building prototype systems and addressing real-world challenges in edge computing and quantum networks.

• Education: PhD from Dartmouth College under Daniela Rus

Research interests span edge computing architecture, secure deep learning, federated learning, and quantum computing applications. His Edge Computing Group explores scalable solutions for distributed systems and privacy-preserving technologies.

Recent publications (2022-2024) focus on quantum networks, federated learning robustness, and privacy-preserving algorithms. A notable trend is integrating quantum computing with edge systems for enhanced security and efficiency.

• Awards: NSF Career Award (year unspecified), IEEE Fellow (year unspecified)

Advised students have transitioned to academia and industry roles, reflecting Li's mentorship impact. Active in conference organization, he has led program committees for ACM SEC and IEEE ICDCS, while steering editorial boards in computer networks and systems. Current projects include quantum network routing and Byzantine-tolerant federated learning.