About Me
Dr. Xishun Liao is currently an Assistant Professor at the University of Central Florida (UCF), affiliated with the Knights Digital Twin Initiative and the Department of Civil, Environmental and Construction Engineering. He earned his Ph.D. in Electrical and Computer Engineering from UC Riverside in 2023, under the guidance of Dr. Matthew J. Barth and Dr. Guoyuan Wu. Previously, Dr. Liao served as a Research Scientist at the UCLA Mobility Lab, where he led cutting-edge research in AI and mobility digital twins. With a multidisciplinary background including working experience in Civil&Environmental Engineering Department, degrees in both Electrical&Computer Engineering and Mechanical Engineering, Dr. Liao brings a unique perspective to mobility research. He has authored 0+ peer-reviewed publications and received notable recognition for his work, including showcasing his innovations at the Consumer Electronics Show (CES) and earning the prestigious Best Paper Award from the IEEE Intelligent Transportation Systems Society (IEEE ITSS) at ITSC 2024. His interdisciplinary expertise spans artificial intelligence, digital twin technology, and intelligent transportation systems, contributing to the next generation of smart mobility solutions.
Research Interests
🌐 Digital Twin of Mobility System
Developing comprehensive digital twin solutions for urban mobility, with a focus on designing and implementing Digital Twin Systems and Internet of Things (IoT) infrastructure. My goal is to create safer, more efficient, and sustainable transportation systems through advanced data science and ML/AI technologies.
🚗 Human and Vehicle Digital Twin: AI Agent Modeling
Creating digital replicas/simulacra of human and vehicles through advanced AI modeling. This research encompasses human travel behavior analysis, driving behavior prediction, and autonomous driving development, aimed at developing human-centric AI and personalized mobility solutions.
🛣️ Traffic Network Digital Twin: AI Network Modeling
Specializing in digital twin development for traffic networks, focusing on comprehensive network modeling and transportation infrastructure optimization. This work advances data-driven urban mobility solutions through intelligent traffic modeling and optimization techniques.
Education
- Ph.D. in Electrical Engineering 2019-2023 University of California, Riverside
- M.Eng. in Mechanical Engineering 2017-2018 University of Maryland, College Park
- B.Eng. in Mechanical Engineering 2012-2016 Beijing University of Posts and Telecommunications