T-ITS Editorial Board Members

Di Wu Headshot
Di Wu
Associate Editor
Bio:
Di Wu is a Professor with the State Key Laboratory of Advanced Design and Manufacturing for Vehicle Body at Hunan University, China, and the Founder of ExponentiAI Innovation. He is also the Vice Director of the Key Laboratory for Embedded and Network Computing of Hunan Province, the Director of Data Intelligence and Service Collaboration (DISCO) Lab, and the Director of DJI Innovation Lab at Hunan University. He received his Ph.D. in Computer Science from the University of California, Irvine in 2013 with interdisciplinary research background across Computer Science, Communication Engineering, Transportation Systems, Interaction Design, etc. and now holds the position as an Adjunct Researcher at the University of California Transportation Center. Prior to join Hunan University, he was a Research Staff at the Intel Collaborative Research Institute for Sustainable Connected Cites (ICRI-Cities), and a Research Associate in the Department of Computing at Imperial College London. He also had experiences as a Staff Research Associate at the University of California-Irvine, a Student Research Associate at the Stanford Research Institute, and a Visiting Researcher at IBM Research. His research interests include future networking, intelligent analytics, and smart architecture for transportation systems engineering. Dr. Wu has published more than 60 papers in highly-ranked international journals and conferences, such as IEEE T-ITS, IEEE TII, IEEE TON, IEEE TC, IEEE TMC, IEEE TPDS, IEEE INFOCOM, ACM UbiComp, TRB, etc. He has been serving as associate editor for IEEE Transactions on Intelligent Transportation Systems, guest editor for IEEE Access, active reviewer for more than 10 top-tier international journals, and TPC member for more than 20 well-known international conferences. He is a member of IEEE, ACM and CCF.
Research Interests
1. Future Networking: Crowdsensing, Mobile IoT/V2X, and 5G Communications2. Intelligent Analytics: Temporal-Spatial Data, Deep Learning, and Real-Time Embedded Systems 3. Smart Architecture: Cyber-Physical-Social Systems, Cloud-Edge-End Computing, and Programmable Cities