Keynote Speaker Ⅰ

Professor Mehrdad Dianati

Queen's University of Belfast

Biography: Mehrdad Dianati is a professor of Connected and Autonomous Systems at the Queen’s University of Belfast. He is also a part-time professor of Intelligent Vehicles at the University of Warwick, where he was the Head of the Intelligent Vehicles Research Department and the Technical Research Lead in Networked Intelligent Systems at the Warwick Manufacturing Group (WMG), the University of Warwick, UK. He also served as the Director of Warwick's Centre for Doctoral Training on Future Mobility Technologies, training doctoral researchers in intelligent and electrified mobility systems in collaboration with the experts in the field of electrification from the Department of Engineering of the University of Warwick. He was a Fellow of the Alan Turing Institute from 2021 to 2023. He is currently the Field Chief Editor of Frontiers in Future Transportation. His research focuses on the application of Digital Technologies (Information and Communication Technologies and Artificial intelligence) for the development of future mobility and transport systems. He has over 30 years of combined industrial and academic experience, with 20 years in various leadership roles in multi-disciplinary collaborative R&D projects. He works closely with the automotive and ICT industries, which are the primary application domains of his research. In the past, he has served as an Editor for the IEEE Transactions on Vehicular Technology and several other international journals, including IET Communications. 

Speech Title: Trustworthy AI for Autonomous Vehicles

Abstract: Modern vehicles are increasingly becoming complex, intelligent systems that use various digital technologies and AI to offer smart features such as automated driving, smart/adaptive infotainment, and maintenance/support in full integration with the offboard digital infrastructures. These features provide higher levels of automation to relieve the human driver from tedious tasks and improve vehicle safety and efficiency. However, as the automation level increases, gaining the trust of the users and other stakeholders in the underlying technologies becomes increasingly complex and crucial for the successful adoption of future intelligent vehicles. Trust is a multifaceted concept, one of them being resilience, i.e., the system’s ability to operate safely when something goes wrong. A crucial enabler of resilience is automated integrity monitoring to recognize internal system faults or unacceptable performance by various system elements due to external factors. To this end, the focus of this presentation is on automated integrity monitoring for AI systems in Intelligent Vehicles, elaboration of its challenges and the discussion of the potential approaches that can be adopted in intelligent vehicles.