Li Ang

Dr. Li Ang is an Assistant Professor in the Department of Electrical and Computer Engineering at the University of Maryland, College Park. He joined UMD in August 2023 as a tenure-track faculty member. Prior to this, he was a Research Associate at Qualcomm AI Research and completed his Ph.D. in Electrical and Computer Engineering at Duke University in 2022, alongside another Ph.D. in Computer Science from the University of Arkansas. His research focuses on the intersection of machine learning and edge computing, emphasizing large-scale networked and trustworthy intelligent systems. Dr. Li has received notable awards, including the IEEE TCCPS Outstanding Ph.D. Dissertation Award, ACM KDD Best Student Paper Award, and the Cisco Research Award.

• Ph.D. in Electrical and Computer Engineering, Duke University (2022)
• Ph.D. in Computer Science, University of Arkansas
• MS in Management of Innovation and Venture Capital, Peking University
• Bachelor's in Computer Science, Henan University, China

His research interests are centered at the intersection of machine learning and edge computing. He focuses on developing large-scale networked and trustworthy intelligent systems that address practical challenges in a collaborative, scalable, secure, and ubiquitous manner. Key areas include federated learning, distributed machine learning, edge computing, AI for IoT, and ensuring the trustworthiness of machine learning systems through fairness and robustness.

Dr. Li has been recognized with several prestigious awards and honors:

• IEEE TCCPS Outstanding Ph.D. Dissertation Award
• ACM KDD Best Student Paper Award (2020)
• Duke ECE Department Outstanding Dissertation Award (2022-2023)
• Cisco Research Award (2025)
• Invited as an Associate Editor of IEEE Transactions on Neural Networks and Learning Systems (TNNLS)
• Distinguished Paper Award at ACM CCS’24 (2024)

Dr. Li advises several doctoral and master’s students, including notable advisees Guoheng Sun and Shwai He, who have received the Qualcomm Innovation Fellowship. He actively seeks motivated students to join his research group. His work has been supported by grants such as the Cisco Research Award and he has been involved in various collaborations, including with Qualcomm AI Research and academic institutions.

Dr. Li leads a research group focused on edge intelligence and federated learning. His work often involves interdisciplinary collaborations, leveraging expertise in machine learning, systems, and distributed computing to advance practical AI solutions. Key projects include developing efficient federated learning frameworks and exploring trustworthy AI systems for edge devices.