Chun-Hung Liu, Ph.D.
Assistant 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 Assistant 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 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 was a recipient of the Best Paper Award from IEEE Globecom Conference in 2008 and 2014, a recipient of the Excellent Young Scholar Grant Award from the Ministry of Science and Technology of Taiwan in 2015, and a recipient of the Outstanding Advisor Award from the Taiwan Institute of Electrical and Electronic Engineering in 2016. He is a senior member of IEEE.
Research Interests
Machine Learning and Its Applications in Wireless Systems
Edge Computing, Intelligence, and Distributed Learning Systems
Data Science
Signal Processing and Image Processing
Cybersecurity
Cyber-physical Systems
Recent News
07/2022: Received a research grant from NSF to work on high-dimensional data analysis and learning from noisy limited data.
07/2022: There will be a couple of PhD research openings in my group starting from Spring/Fall 2023. Interested students who have good background in machine learning, networking, and statistics feel free to send your resume to me. I will reply you if you are a good fit for the openings.
07/2022: Received a research grant from AFRL to work on spectrum sensing and learning problems in UAV-enabled networks with intelligent reconfigurable surfaces.
03/2022: Our paper entitled "Modeling and Analysis of Intermittent Federated Learning Over Cellular-Connected UAV Networks" was accepted by IEEE VTC Spring 2022.
Research Topics
Topic I: Distributed Learning over Ultra-Dense Wireless Networks with Repulsion
Topic II: Machine Learning for 6G Wireless Systems
Topic III: Federated Sensing, Learning, and Security for Large-Scale Wireless CPSs
Topic IV: High-Dimensional Data Analysis and Large-Scale Learning
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. 2020. (ISBN-10: 1839530790)
Journal Articles
Learning over Large-Scale Networks and Data Analysis
Distributed Estimation, Control, Security, and Learning
C.-H. Liu and C.-T. Kuo, "Distributed Secure Kalman Filtering in a Poisson Field of Attackers", submitted to IEEE Trans. on Signal Processing, Dec. 2021. (Under Revision)
C.-H. Liu, "Secure Estimation and Control in Wireless Cyber-Physical Systems: A Reinforcement Learning Approach", submitted to IEEE Trans. on Control of Network Systems, Nov. 2021. (Under Revision)