【SDS系列学术讲座】Efficient, Safe, Trustworthy and Causal Autonomous Systems
主题：Efficient, Safe, Trustworthy and Causal Autonomous Systems
报告人：Dezong ZHAO, Senior Lecturer, James Watt School of Engineering, University of Glasgow
主持人：Junfeng WU, Associate Professor, School of Data Science, CUHK-Shenzhen
日期：30 June, 2023
时间：3:00 PM to 4:00 PM, Beijing Time
The main challenge in autonomous driving is to handle uncertainties. It proposes rigorous requirements that autonomous vehicles need to guarantee safe and trustworthy decision making. To make the decision making realistic, autonomous vehicles have to be interpretable, adaptable, verifiable and robust. The goals would be achieved by developing transparent and reliable tools in perception, planning, modelling and control. Moreover, the current autonomous vehicles are power hungry so green driving solutions are expected. To this end, developing ecological driving strategies and event-camera-based perception falls into our research interest.
Dezong Zhao is a Senior Lecturer in Autonomous Systems at James Watt School of Engineering, University of Glasgow. He was awarded an EPSRC Innovation Fellow in 2018 and a Royal Society-Newton Advanced Fellow in 2020. His research focuses on perception, decision making, modelling and control of connected and automated vehicles. He is a Senior Member of IEEE, a Member of IET and SAE, and a Fellow of HEA. He is the Deputy Head of the Autonomous Systems and Connectivity Research Division, a Full Member of the EPSRC Review College and a Member of the UKRI Future Leader Fellow Review College. He has over 80 papers published in leading journals and peer review conferences. He has secured grants as the PI from EPSRC, The Royal Society and industry. He was the TPC member of 6 peer-review conferences and chaired 3 sessions. He has won multiple awards including the Best Paper Award at the ICUS in 2021, the Best Poster Prizes at the FPC in 2019 and 2018, and the IEEE CDC Young Researcher Award in 2015. He is an Associate Editor of IEEE TIV and IEEE TVT.