Speakers 2024

Keynote Speaker Ⅰ

Prof. Changxu Wu

Tsinghua University, China

Brief Introduction: Dr. Wu is interested in integrating cognitive science and engineering system design, especially quantifying human cognition system with mathematical models and symbolic models with their applications in system design, improving transportation safety, promoting human performance and safety in human-machine interaction and healthcare, and inventing innovative sustainable and smart energy systems with human in the loop. Dr. Wu has over 140 peer-reviewed publications with over 3,666 citations including 100 journal papers, 40 conference papers, 1 book (In Press), 2 book chapters, 8 patents (4 authorized patents, 4 pending), and 1 utility model pending. He also leads several multidisciplinary research teams and projects funded by NSF China (1 CNSF national key project with RMB 1,200,000), 4 major NSF grants in USA, NIH (1 NIH), UTRC (3 UTRC), and industries.

Keynote Speaker Ⅱ

Assoc. Prof. Chen Lv

Nanyang Technological University, Singapore

Brief Introduction: Chen Lv is an Associate Professor at School of Mechanical and Aerospace Engineering, and the Cluster Director in Future Mobility Solutions, Nanyang Technological University, Singapore. He received his PhD degree at Department of Automotive Engineering, Tsinghua University in 2016, with a joint PhD at EECS Department, University of California, Berkeley. He was a Research Fellow at Cranfield University, UK during 2016-2018. He joined NTU as a Nanyang Assistant Professor and founded the Automated Driving and Human-Machine System (AutoMan) Research Lab in June 2018, and got promoted to Associate Professor with Tenure in August 2023. His research focuses on AI, robotics, automated driving, and human-machine systems, where he has published 4 books, over 100 papers, and obtained 12 granted patents. He serves as Associate Editor for IEEE Transactions on Intelligent Transportation Systems, IEEE Transactions on Vehicular Technology, IEEE Transactions on Intelligent Vehicles, etc. He received many awards and honors, selectively including IEEE IV Best Workshop/Special Session Paper Award (2018), Automotive Innovation Best Paper Award (2020), Winner of Waymo Open Dataset Challenges at CVPR (2021, 2022), Winner of IEEE VTS Motor Vehicles Challenge (2022), Machines Young Investigator Award (2021), Nanyang Research Award (Young Investigator) (2022), Most Innovative Award of NeurIPS Driving SMARTS Competition (2022), SAE Ralph R. Teetor Educational Award (2023), CVPR nuPlan Planning Challenge Innovation Prize (2023), and IEEE ITSC 2023Best Paper Runner-Up Award.

Speech Title: Human-like Autonomy for Smart Mobility and Robotics

Abstract: The long-term goal of artificial intelligence (AI) systems is to make them learn, think and act smartly like human beings. As a typical application of AI, autonomous vehicles (AVs) become one of the most potential and ultimate ambitions in the smart mobilities. They primarily designed to replace human drivers during driving in order to enhance the performance and avoid the possible fatalities. In the near future, AVs are believed to share public roads with human-driven vehicles, which requires AVs to be smart and able to behave like human drivers, being reasonable and predictable to other road users. However, due to their limited smartness, current AVs are still lack of robust situation understanding, interaction prediction and human-like decision-making abilities when interacting with others, particularly in complex and emergency situations. Therefore, human-machine hybrid intelligence, as well as human-machine collaboration, are of great importance to ensure the safety and further improve the smartness of mobility systems, during long-term development and large-scale deployment of AVs. In this talk, the recent studies in human-like autonomy and human-machine hybrid intelligence for future mobility will be presented. First, a data-driven prediction and decision-making framework for human-like autonomous driving will be introduced. Next, a novel human-machine collaboration framework with bi-directional performance augmentation ability developed for automated vehicles and robotics will be presented in detail.

Keynote Speaker Ⅲ

Prof. Yang Cong

South China University of Technology, China

Keynote Speaker Ⅳ

Prof. Xiaolong Zheng

Institute of Automation, Chinese Academy of Sciences, China

More speakers are to be announced......