معرفی
Chun-Hung Liu is an Associate Professor in the Department of Electrical and Computer Engineering at Mississippi State University (MSU). He previously held positions at the University of Michigan, National Chiao Tung University, and Qualcomm Inc. His research focuses on machine learning theory, stochastic control, data science, wireless communication, and cyber-physical systems security. Prof. Liu has received prestigious awards including the Air Force Research Lab Faculty Fellowship (2023), Taiwan’s Young Scholar Award (2015), and an IEEE Globecom Best Paper Award (2014).
- Education:
- Ph.D., Electrical and Computer Engineering, University of Texas at Austin
- M.S., Mechanical Engineering, MIT
- M.S., Electrical Engineering, National Taiwan University
- B.S., Mechanical Engineering, National Taiwan University
Research Interests: Dr. Liu’s work spans theoretical and applied domains, including deep learning topology analysis, edge computing optimization, federated learning architectures, and underwater acoustic communication systems. He explores practical solutions for energy-efficient computing, cyber-physical system security, and next-generation wireless networks (e.g., 5G/6G, RIS-enabled systems).
Publications: His recent work emphasizes interdisciplinary approaches, with articles addressing topics like RIS-assisted MIMO systems, federated learning over UAV networks, and solar-powered edge computing. These studies highlight innovations in both algorithm design and system-level performance evaluation.
- Awards:
- Air Force Research Lab Faculty Fellowship (2023)
- Taiwan’s Young Scholar Award (2015)
- IEEE Globecom Best Paper Award (2014)
Advising & Grants: While specific grant details are not provided, his publications indicate sustained research activity supported by military and academic collaborations. His lab focuses on experimental platforms for federated learning and wireless mesh networks, as evidenced by a mini-PC-based testbed described in 2022 work.
Labs/Teams: Leads a research group at MSU investigating edge computing, federated learning, and reconfigurable intelligent surface technologies. Collaborates with industry partners (e.g., Qualcomm) and international institutions on communication systems and AI integration.
