Chun-Hung Liu, Ph.D.
Associate Professor
Dept. of Electrical and Computer Engineering
Mississippi State University
Mississippi State, MS 39762, USA
e-mail: chliu at ece dot msstate dot edu
Phone (O): (662) 325-2063
Brief Biography
Dr. Liu is an Associate Professor in the Department of Electrical and Computer Engineering at Mississippi State University (MSU). Prior to joining MSU, he was with University of Michigan and National (Yang Ming) Chiao Tung University, Hsinchu Taiwan. He received a B.S. degree from National Taiwan University, an M.S. degree from Massachusetts Institute of Technology, and a Ph.D. degree in Electrical and Computer Engineering from the University of Texas at Austin. He received several prestigious awards in research and education, such as Faculty Research Award from Air Force Research Lab. (AFRL) in 2023, Outstanding Advisor Award from the Taiwan Institute of Electrical and Electronic Engineering in 2016, Young Scholar Research Award from the Ministry of Science and Technology of Taiwan in 2015, Best Paper Awards from IEEE Globecom Conference in 2014 and 2008, etc. He is a senior member of IEEE.
Research Interests
Machine Learning Theory and Its Applications
Data Science: Analysis and Learning of High-Dimensional Noisy Data
(Large-Scale) Optimization, Control, and Reinforcement Learning
(Wireless) Communication, Networking, and Signal Processing
Quantum Commputing and Communication
Recent News
9/2023: There will be a couple of Ph.D. research openings in my group starting from Spring 2024. Interested students who have good background in machine learning, networking, probability, and statistics feel free to send your resume to me. I will reply to you if you are a good fit for the openings.
Research Topics
Topic I: Learning over Ultra-Dense Wireless Networks with Repulsion (funded by NSF)
Topic II: Analysis and Adversarial Learning of High-Dimensional Noisy Data (funded by NSF)
Topic III: Adaptable Spectrum Sensing and Learning for UAV-enabled Wireless Networks with Intelligent Reconfigurable Surfaces (funded by AFRL)
Topic IV: Federated Learning for Cybersecurity in Wireless CPSs (funded by AFRL/DHS)
The detailed information of the above topics can be found here.
Selected Publications
Recent Book Chapter
Deep Learning and Federated Learning Toward 6G Mobile Communications in the new book entitled "Flexible and Cognitive Radio Access Technologies for 5G and Beyond", the Institution of Engineering and Technology, Oct. 2021. (ISBN-10: 1839530790)