Keynote Speakers
Peng Shi
Website | ORCID | Google Scholar
University of Adelaide, Faculty of Engineering, Computer and Mathematical Sciences, Australia
Keynote Talk: From Model-based to AI-Empowered Cyber-Physical Multi-Agent Systems
(Monday, October 6, 09:30-10:30, Hall F)
Cyber-physical multi-agent systems (CPMAS) integrate various autonomous systems, and even human participants, through both cyber-layer communication and physical-layer collaboration, enabling them to operate collectively in complex, open environments. Traditionally, these systems have relied on model-based control methods to ensure robust coordination and reliable performance. However, recent advances in artificial intelligence (AI) offer promising opportunities to enhance autonomy, adaptability, and scalability when faced with various constraints at both the cyber and physical layers—such as malicious cyberattacks and internal system faults. This talk illustrates the technological evolution from model-based approaches to AI-empowered frameworks for CPMAS, highlighting how data-driven techniques—such as reinforcement learning, deep neural networks, and bio-inspired AI—can address limitations in traditional design and control frame. We will explore the challenges of seamlessly integrating model-driven and AI-driven strategies, including stability, safety, and security. By combining advanced control methodologies with emerging AI capabilities, we present a series of experimental case studies that verify our proposed techniques with potential real-world applications in intelligent manufacturing, autonomous vehicles, and smart infrastructure. Ultimately, this talk provides insights into the future of CPMAS, setting the stage for innovative research and practical deployments.
Biography
Peng Shi is a Distinguished Professor, and Director of Laboratory of Advanced Unmanned Systems at the University of Adelaide, Australia. His research interests include systems and control theory and applications to autonomous and robotic systems, intelligence systems, and cyber-physical systems. His work has received, 100000+ citations from Google Scholar. He has received many recognitions for his research achievements, including the Nobert Wiener Award from IEEE SMC Society in 2024, the Annual Scientific Award, and Ramesh Agarwal Life-time Achievement Award from the International Engineering and Technology Institute in 2024 and 2023, the M. A. Sargent Medal Award from Engineers Australia in 2022, the Highly-Cited Researcher from Thomson Reuters in both fields of engineering and computer science from 2014-2024, the Lifetime Achiever Leader-Board and Field Leader recognition from THE AUSTRALIAN Research Review from 2019-2024, the Outstanding Research Achievement Award from the University of Adelaide in 2020, the Chancellor’s Gold Medal Award for Outstanding Research Performance from Victoria University in 2018, and the Andrew Sage Best Transaction Paper Award from IEEE SMC Society in 2016.
He is a Fellow of IEEE, IET, IETI, IEAust, CAA, a Distinguished Lecturer of IEEE SMC Society, and a Member of the Academia Europaea. He serves/served as editorial board member for many journals, such as Automatica, IEEE Transactions on (Automatic Control; Artificial Intelligence; Fuzzy Systems; and Circuits and Systems). He is now the Editor-in-Chief of IEEE Transactions on Cybernetics, and a Senior Editor of IEEE Access. His other professional experience includes as Senior Scientist at Defence Science and Technology Organisation, Australia, Professor at University of Glamorgan, UK, and Victoria University, Australia,
He received the PhD degree in Electrical Engineering from the University of Newcastle, Australia in 1994, and the PhD degree in Mathematics from the University of South Australia in 1998. He also received the Doctor of Science degree from the University of Glamorgan, UK in 2006, and the Doctor of Engineering degree from the University of Adelaide, Australia in 2015.
John Krumm
Website | LinkedIn | ORCID | Google Scholar
Viterbi School of Engineering, University of Southern California, United States
Keynote Talk: Personal Data Privacy – Especially Location
(Tuesday, October 7, 10:30-11:30, Hall F)
We generally give away our personal for free on the web. While technologies like differential privacy can protect our aggregated data, the holders of our data can still use it to make individual inferences about us that might be alarming. This talk will demonstrate some of these inferences for location data (GPS tracks) and for more general personal data as a first step to understanding and reducing the privacy risks. This leads to a study to see if people become more concerned about the privacy of their personal data if they know what could be inferred from it. Finally, I’ll discuss how we can compute a specific price for individual location points so people could sell their location data rather than give it away.
Biography
John Krumm graduated from the School of Computer Science at Carnegie Mellon University in 1993 with a PhD in robotics and a thesis on texture analysis in images. He worked at the Robotics Center of Sandia National Laboratories in Albuquerque, New Mexico for the next four years. His main projects there were computer vision for object recognition for use in robots and vehicles. He was at Microsoft Research in Redmond, Washington, USA for 25 years, starting in 1997. He is currently an associate director of the Integrated Media Systems Center in the Viterbi School of Engineering at the University of Southern California. His research focuses on understanding peoples' location and personal data privacy. In 2017 he received a 10-year impact award for a paper on location privacy from the ACM UbiComp conference, and another from the same conference in 2021. He received the best paper award at the ACM SIGSPATIAL conference in 2022 and at the Mobile Data Management conference in the same year. His h-index on Google Scholar is 75. He is an inventor on 82 U.S. patents. Dr. Krumm was a PC chair for UbiComp 2007, ACM SIGSPATIAL 2013, and ACM SIGSPATIAL 2014. He is a past coeditor in chief of the Journal of Location Based Services and past associate editor for ACM Transactions on Spatial Algorithms and Systems. He currently serves on the editorial board of IEEE Pervasive Computing Magazine. He is the chair of the executive committee of ACM SIGSPATIAL and part of the Science Advisory Committee of the Geospatial Science and Human Security Division at Oak Ridge National Laboratory. He is an editorial fellow for the Paris Institute for Advanced Study.
Dimitar Filev
Website | LinkedIn | ORCID | Google Scholar
Ford Research & Advanced Engineering (retired) / Hagler Institute for Advanced Study, Texas A&M University, United States
Keynote Talk: Driving Innovation: AI in Automotive Engineering
(Wednesday, October 8, 10:45-11:45, Hall F)
Artificial Intelligence (AI) is rapidly transforming the automotive industry. From enhancing vehicle performance and safety to streamlining manufacturing processes, AI-powered systems are driving significant advancements. This presentation, drawing on the speaker's 30+ years of experience in R&D, discusses the transformative role of AI in various automotive applications. We will explore the evolution of AI in the automotive sector, from early AI to deep learning and generative AI. We will examine the challenges and opportunities associated with integrating AI solutions. The presentation will highlight specific examples of AI applications in powertrain, vehicle systems, and autonomous driving. We will examine the lessons learned from applying data-driven AI techniques and discuss the potential of combining knowledge-based approaches with data-driven methods to further enhance AI's impact on the automotive industry.
Biography
Dimitar Filev is Senior Henry Ford Technical Fellow in Control and AI at Ford Motor Company (retired). He is currently a Fellow of the Hagler Institute for Advanced Study, Texas A&M University. His research is focused on computational intelligence, AI and intelligent control, and their applications to autonomous driving, vehicle systems, and automotive engineering. He holds 140 granted US patents and has over 200 publications with 21,000+ citations and h-index of 63. He has been awarded 6 times the Henry Ford Technology Award, the IEEE Systems, Man & Cybernetics 2008 Norbert Wiener Award, the 2015 IEEE Computational Intelligence Pioneer’s Award, and 2023 IEEE SMCS Wohl Outstanding Career Awar. Dr. Filev is a member of the National Academy of Engineering and a Life Fellow of the IEEE. He was President of the IEEE Systems, Man, & Cybernetics Society (2016-2017). He received his PhD. in EE from the Czech Technical University, Prague in 1979.
