Thomas Tie Luo

Thomas Tie Luo is a tenured Associate Professor in the Department of Electrical and Computer Engineering and a courtesy joint appointee in the Department of Computer Science at the University of Kentucky, within the Stanley and Karen Pigman College of Engineering. Previously, he served as an Associate Professor at Missouri University of Science and Technology. He holds a Ph.D. in Electrical and Computer Engineering from the National University of Singapore.

• Ph.D., Electrical and Computer Engineering, National University of Singapore

His research focuses on Trustworthy Artificial Intelligence, particularly in healthcare, medicine, and the Internet of Things (IoT). Key areas include explainable AI (XAI), adversarial and robust machine learning, security and privacy in federated learning, and time series analysis. He develops both theoretical models and real-world systems, such as federated satellite learning frameworks and anomaly detection platforms for edge computing. His work bridges deep learning with practical applications in medical imaging, dementia detection, and secure IoT environments.

The recent publications (2023–2025) demonstrate a strong trend in advancing federated learning for satellite and edge networks, enhancing model interpretability in healthcare, and improving adversarial robustness in deep learning. These works appear in top-tier venues like AAAI, PAKDD, IEEE JSAC, and PerCom, often receiving recognition through best paper awards. His research integrates computer vision, signal processing, and secure distributed learning, reflecting a multidisciplinary approach to trustworthy AI.

His scientific achievements have been recognized with multiple awards, including:

• Best Paper Award at PAKDD'25 workshop
• Best Paper Runner-Up at PAKDD'24
• Best Paper Runner-Up at PerCom'24
• Best Student Paper Award at AAIM'18
• Best Paper Award at ICTC'12
• Best Paper Finalist at INFOCOM'15

Dr. Luo advises PhD students in computer science, electrical engineering, and computer engineering. He has successfully mentored several doctoral graduates now in academic and industry roles, including Assistant Professors and Research Scientists at institutions like Washington State University and ByteDance. He has served as a grant panelist for the NSF, U.S. Department of Energy, and Euregio Science Fund, and as an external evaluator for faculty promotion at the University of Washington. His editorial roles include Area Editor for Pervasive and Mobile Computing and Ad Hoc Networks, and Associate Editor for several journals.

He leads research efforts involving real testbeds and system implementations, such as federated learning frameworks for LEO satellite networks and lightweight object detection systems like YOGA. His lab emphasizes not only algorithmic innovation but also practical validation through deployed systems in edge computing, IoT, and mobile crowdsensing.