Rate My Professor Liang Zhao

Liang Zhao is an Assistant Professor of Information Technology in the College of Computing and Software Engineering at Kennesaw State University, where he serves as a SunTrust Faculty Fellow. He earned his Ph.D. in Computer Science from Georgia State University and his M.S. in Electrical Engineering from Lehigh University. Before joining KSU, Dr. Zhao worked as a research data scientist at IBM. His research spans cybersecurity, big data computing and analytics, and machine learning, with a focus on efficient and secure computing frameworks for Cyber-Physical Systems and the Internet of Things. Ongoing projects include federated learning for detecting false data injection attacks in solar farms, communication-efficient semi-hierarchical federated analytics in IoT networks, vibration sensing-based human and infrastructure safety and health monitoring, hybrid decentralized data analytics in edge computing empowered IoT networks, and privacy-preserving distributed analytics in fog-enabled IoT systems. In 2024, he received a $51,747 NIH AIM-AHEAD grant to investigate health factors related to obesity using AI and machine learning, analyzing social determinants of health from large datasets like the OCHIN database covering over six million patients to build predictive models for rural communities.

Dr. Zhao has authored numerous publications in leading journals and conferences. Selected works include "A Federated Learning Framework for Detecting False Data Injection Attacks in Solar Farms" (IEEE Transactions on Power Electronics, 2021), "Communication-Efficient Semi-Hierarchical Federated Analytics in IoT Networks" (IEEE Internet of Things Journal, 2021), "Hybrid Decentralized Data Analytics in Edge Computing Empowered IoT Networks" (IEEE Internet of Things Journal, 2020), "Privacy-Preserving Distributed Analytics in Fog-Enabled IoT Systems" (Sensors, 2020), "Fast Decentralized Data Analytics in IoT Wireless Networks" (IEEE Access, 2019), and "Communication-Efficient Decentralized Algorithms for Seismic Tomography With Sensor Networks" (International Journal of Parallel, Emergent and Distributed Systems, 2019). He earned the Best Student Paper Award at the IEEE Innovative Smart Grid Technologies Conference-Asia in 2014 for "Topology Identification in Smart Grid with Limited Measurements Via Convex Optimization." His work advances distributed analytics and security in IoT, CPS, smart grids, and healthcare applications.