Generative AI is redefining smart IoT ecosystems by embedding reasoning and intelligent decision-making capabilities directly into physical devices and systems. Through embodied intelligence, IoT devices are evolving from passive data collectors into active agents capable of predicting physical interactions and dynamically adapting to environmental changes, user behaviors, and system dynamics. In this talk, I will present our recent research on world model–based autonomous driving (AD) as a compelling example of this transformation. By leveraging the ability to extrapolate and anticipate outcomes in previously unseen situations, world model–based agents embody the generative and predictive strengths of AI, making them particularly adept at tasks that demand foresight and planning. Their self-supervised learning and proactive decision-making capabilities enable autonomous systems to go beyond reactive control, reasoning instead about the future. I will also introduce CarDreamer, our open-source reinforcement learning platform that integrates world models with CARLA to advance research in autonomous driving. In summary, we envision that smart IoT systems will evolve into an Internet of Agents—a connected ecosystem of intelligent, adaptive, and proactive entities shaping the physical world through generative intelligence.

Junshan Zhang has been a professor in the ECE Department and CS graduate faculty at University of California Davis since 2021. He received his Ph.D. degree from the School of ECE at Purdue University in Aug. 2000, and was on the faculty of the School of ECEE at Arizona State University from 2000 to 2021. His research interests fall in the general field of information networks and data science, including edge AI, reinforcement learning, world model, continual learning, wireless networks, information theory. He is a Fellow of National Academy of Inventor (class of 2024) and the IEEE (class of 2012), and a recipient of the ONR Young Investigator Award in 2005 and the NSF CAREER award in 2003. His papers have won a few awards, including the Best Student paper at WiOPT 2018, the Kenneth C. Sevcik Outstanding Student Paper Award of ACM SIGMETRICS/IFIP Performance 2016, the Best Paper Runner-up Award of IEEE INFOCOM 2009 and IEEE INFOCOM 2014, and the Best Paper Award at IEEE ICC 2008 and ICC 2017. He is currently serving as Editor-in-Chief of IEEE/ACM Transactions on Networking.

This presentation explores how the convergence of distributed systems and generative AI is revolutionizing modern medicine. By enabling real-time, scalable, and privacy-preserving analytics, these technologies support breakthroughs in diagnostics, personalized treatment, surgical robotics, and drug discovery. Case studies in federated learning and pandemic response demonstrate clinical efficacy and global scalability. The talk also addresses ethical challenges, data equity, and future research directions. Together, distributed computing and generative modelling form a transformative healthcare infrastructure—decentralized yet intelligent—designed to enhance patient outcomes and democratize access to cutting-edge medical innovations across institutional and geographic boundaries.

Albert Y. ZOMAYA is the Peter Nicol Russell Chair Professor of Computer Science at the University of Sydney and Director of the Centre for Distributed and High-Performance Computing. A global leader in parallel and distributed systems, he has authored more than 800 publications and 30 books, shaping the field’s research agenda for over three decades. He is a Fellow of the IEEE, the Australian Academy of Science, and the Royal Society of New South Wales, and an elected member of Academia Europaea and the European Academy of Sciences and Arts. Professor Zomaya previously served as Editor-in-Chief of IEEE Transactions on Computers, IEEE Transactions on Sustainable Computing, and ACM Computing Surveys. His work spans parallel and distributed computing, networking, and complex systems, with a lasting influence on both theory and practice.

To Be Announced

Prof. Cao is currently the Otto Poon Charitable Foundation Professor in Data Science and the Chair Professor of Distributed and Mobile Computing in the Department of Computing at The Hong Kong Polytechnic University (PolyU), Hong Kong. He is also the Dean of Graduate School, the director of Research Institute for Artificial Intelligence of Things (RIAIoT) in PolyU, the director of the Internet and Mobile Computing Lab (IMCL) . He was the founding director and now the director of PolyU's University's Research Facility in Big Data Analytics (UBDA). He served the department head from 2011 to 2017. Prof. Cao is a member of Academia Europaea, a fellow of the Hong Kong Academy of Engineering Science, a fellow of IEEE, a fellow of China Computer Federation (CCF) and an ACM distinguished member.

Prof. Cao's research interests include distributed systems and blockchain, wireless sensing and networking, big data and machine learning, and mobile cloud and edge computing. He published 5 co-authored and 9 co-edited books, and over 500 papers in major international journals and conference proceedings. He also obtained 16 patents. Prof. Cao received many awards for his outstanding research achievements, including the PolyU President Award for Excellent Performance/Achievement in Research and Scholarly Activities, Ministry of Education Higher Education Outstanding Scientific Research Output Awards – Natural Science (Second Class), China Computer Federation (CCF) Overseas Outstanding Contribution Award, IEEE TCCLD Research Innovation Award, Hong Kong ICT Awards: Best Innovation & Research - Certificate of Merit and Special Mention, Bronze Medal Award of Brussels Innova, CVIC SE Software Talent Award, Ministry of Education Nominated State Science and Technology Award (First Class), National Science and Technology Progress Award (Second Class), and best paper Awards from IEEE Trans. Industrial Informatics 2018, IEEE DSAA 2017, IEEE SMARTCOMP 2016, IEEE/IFIP EUC 2016, IEEE ISPA 2013, IEEE WCNC 2011, etc. Prof. Cao has delivered over 50 keynote speeches / invited talks.

Prof. Cao has directed and participated in over 130 research and development projects and, as a principal investigator, obtained over HK$67 million grants from funding agencies such as National Natural Science Foundation of China (NSFC), Ministry of Science and Technology of P. R. China (MOST), Hong Kong Research Grant Council (RGC), Hong Kong Innovation and Technology Commission (ITC), The Society of Hong Kong Scholars, and industries and organizations like Alibaba, IBM, Nokia, HK Jocky Club and Hong Kong Construction Industry Council.

Prof. Cao served the Chair of the Technical Committee on Distributed Computing of IEEE Computer Society 2012-2014, a member of IEEE Fellows Evaluation Committee of the Computer Society and the Reliability Society, a member of IEEE Computer Society Education Awards Selection Committee, a member of IEEE Communications Society Awards Committee, and a member of Steering Committee of IEEE Transactions on Mobile Computing. Prof. Cao has also served as chairs and members of organizing and technical committees of many international conferences, including IEEE INFOCOM, IEEE PERCOM, IEEE IoTDI, IEEE ICPADS, IEEE CLOUDCOM, SRDS and OPODIS, and as associate editor and member of the editorial boards of many international journals, including IEEE TC, IEEE TPDS, IEEE TBD, IEEE IoT Journal, ACM ToSN, ACM TIST, ACM TCPS. Prof. Cao has also actively served Hong Kong local professional communities, including Entrepreneurship Advisor of HK A.I. Lab., member of HK Innovation and Technology Fund Research Projects Assessment Panel, member of Engineering Panel of Hong Kong Research Grant Council, member of Incu-Tech Business Incubation Programme Panel of Hong Kong Science and Technology Parks, and member of HKIE's Accreditation Committee for Computer Science Programmes.

Prof. Cao is one of the Academicians of PolyU.

Our daily movements disclose plenty of sensitive information about us - from our habits to religious and political opinions. At the same time, location trajectories are helpful for various applications such as city planning, pandemic control, or marketing. Therefore, numerous approaches for protecting the privacy of trajectory data have been proposed. Nevertheless, recent works show that we are still far from our goal of releasing high-quality trajectories for arbitrary applications under strong guarantees. This talk will provide an overview of location trajectories and their privacy protection. First, we explore whether existing protection mechanisms hold up to their promises in the age of AI. Through a deep learning-based reconstruction attack, we show that even mechanisms using the de facto privacy standard, differential privacy, might be vulnerable. Based on this, we discuss a framework and goals for designing effective privacy protection mechanisms. As we find that the existing protection mechanisms struggle with a restrictive privacy-utility trade-off, we explore whether generating fake data could be the solution. Through a large-scale experimental study, we examine generative models for trajectory data. While their utility is impressive, this research direction still requires future work to satisfy all the set goals.

Salil Kanhere is a Professor at the School of Computer Science and Engineering at UNSW Sydney, Australia. His research interests cover various aspects of cybersecurity, mobile computing, IoT, blockchain, and applied machine learning. He has published over 400 peer-reviewed articles and is leading several government and industry-funded research projects in these areas. He received the Friedrich Wilhelm Bessel Research Award (2020) and the Humboldt Research Fellowship (2014) from the Alexander von Humboldt Foundation in Germany, and has received 12 Best Paper Awards. He is an ACM Distinguished Member, an IEEE Senior Member, and an IEEE Computer Society Distinguished Visitor. He serves on the advisory board of three SMEs and has held visiting positions at RWTH Aachen, I2R Singapore, Technical University Darmstadt, the University of Zurich, and Graz University of Technology. Salil is the Editor in Chief of the Ad Hoc Networks journal and an Associate Editor of IEEE Transactions on Network and Service Management, Computer Communications, and Pervasive and Mobile Computing. He has served on the organising committees of several IEEE/ACM international conferences and is a steering committee member for IEEE LCN and IEEE ICBC. Salil has also co-authored two books.