Keynote Speakers
AI-Mediated Human Interaction
Shalini De Mello
Director of Research, NVIDIA
Abstract:
Humans are innately social creatures with a need to interact with others. The advent of AI has profoundly advanced technologies for human interaction. It has not only opened the doors to seamless human-to-machine interaction but has also helped to significantly enhance human-to-human digital interaction, bringing people together in more engaging and immersive ways. This talk will trace a decade-long progression of the development of cutting-edge AI-mediated technologies for human-to-machine and human-to-human interaction. There are two fundamental aspects to solving this problem — human understanding and human synthesis. This talk will seek to answer the question of how far along we’ve come in solving both, along with what the underlying AI building blocks are that have helped us get here. It will further highlight the successful application areas of AI-mediated human interaction technologies that are positively impacting people’s lives. Lastly, it will conclude with thoughts on what is left on the table in terms of research and innovation and speculate on what the next frontier will be for profound real-world impact in this space.
Bio:Shalini De Mello is a Director of Research, New Experiences and a Distinguished Research Scientist at NVIDIA, where she leads the AI-Mediated Reality and Interaction Research Group. Previously, she was a researcher in the Learning and Perception Research Group at NVIDIA, from 2013 to 2023. Her research interests are in AI, computer vision, computer graphics, human understanding, and digital human synthesis. Her research seeks to use AI to re-imagine interactions between humans, and between humans and machines. She has nearly two decades of experience of both conducting fundamental research to push the boundaries of AI-mediated human interaction and of bringing real world products, based on them, to market. She has co-authored scores of peer-reviewed publications and patents, and serves as an Area Chair for all top-tier AI conferences. Her inventions have contributed to or helped create several NVIDIA AI products, including DriveIX, Maxine and the TAO Toolkit. She received her Doctoral and master’s degrees in electrical and computer engineering from the University of Texas at Austin.
Next Phase of Research on Multimodal Foundation Models
Chua Tat-Seng
KITHCT Chair Professor, School of Computing, National University of Singapore
Abstract:
AI as a concept has been around since the 1950’s. With the recent advancements in machine learning technology, and the availability of big data and large computing resources, the scene is set for the explosive growth of AI. In particular, the emergence of Multimodal Foundation Models that offer significant capabilities in content comprehension, generation, and reasoning has opened up opportunities for multimodal research and applications. The talk first reviews the trends and developments in Multimodal Foundation Models. It then outlines the advances in multilingual and multimodal alignments and discusses the emergence of language- or media-agnostic signals that appear to represent abstract concepts commonly used in human languages. These signals have been shown to have positive impact on both the accuracy and safety of the resulting models. To further improve the performance of the models, most current approaches employ reinforcement learning with various reward functions to achieve better controllable content generation and trust. To facilitate effective reinforcement learning, quality assessment is of pivotal importance while it has largely been over-looked. This talk further presents recent approaches to quality assessment and its role on the generation of videos and 3D media. As research on Multimodal Foundation Models is still in early stage, this talk concludes with directions for future research.
Bio:Dr. Chua is the KITHCT Chair Professor at the School of Computing, National University of Singapore (NUS). He is also the Distinguished Visiting Professor of Tsinghua University, Sichuan University and Zhengzhou University. Dr. Chua was the Founding Dean of the School of Computing from 1998-2000. His research interests include multimodal foundation models, responsible AI, and conversational search and recommendation. He is the co-Director of NExT, a joint research Center between NUS and Tsinghua University.
Dr Chua is the recipient of 2015 ACM SIGMM Achievements Award, 2022 NUS Research Recognition Award, 2024 CCF Overseas Outstanding Technical Contributions Award, and the Fellow of the Singapore National Academy of Science. He is the Chair of the steering committee of Multimedia Modeling (MMM) conference series, and ACM International Conference on Multimedia Retrieval (ICMR) (2015-2018). He was the General Co-Chair of ACM Multimedia 2005, ACM SIGIR 2008, ACM Web Science 2015, WSDM 2023, ACM Web Conference (or WWW) 2024, and the forth coming ACM ICAIF 2025. His group has won many best paper awards, including the recent Outstanding Paper Award at ICLR 2025. He serves on the editorial boards of several international journals. Dr. Chua is the co-Founder of two technology startup companies in Singapore.
SenseCam and Isotyping: The challenges and benefits of working with new hardware
Steve Hodges
Distinguished Professor at Computing and Digital Systems, Lancaster University & Former Research Manager and Principal Researcher, Microsoft
Abstract:
In a world of generative models and large-scale data, this talk revisits the intimate nature and unique value of personal multimedia through the lens of SenseCam—a wearable camera that automatically captures still images to create a visual diary for the wearer. Despite a variety of wearable camera products that have come to market in the decades since SenseCam was conceived, the unique properties of the original prototypes and the benefits these unlocked remain elusive today. Having explored why it is so challenging to move from a hardware prototype like SenseCam to a fully-fledged product, this talk will present a new step in the prototyping-to-production journey called isotyping. Isotyping shines a light on the critical, but often overlooked, steps necessary to scale from a promising prototype towards viable low-volume production. The talk concludes by calling on the research community to help refine the concept and process of isotyping as we collectively continue to explore the potential of new forms of hardware in our research.
Bio:Steve Hodges combines hardware research and engineering skills to conceive novel solutions that make computers more useful, engaging and inclusive. His work spans domains such as education, the internet of things, mobile & ubiquitous computing, and assistive technologies. He operates at all scales from prototype to production, and his work has contributed to over ten million devices with over sixty million users. Steve is also a passionate proponent and communicator of all things tech.Following 25 years working in industry research labs, in 2023 Steve moved to Lancaster University as a Distinguished Professor. He is a fellow of the IEEE, the IET and a member of the ACM SIGCHI Academy. He has been granted 135 patents and has published over 100 top-tier peer-reviewed papers with nearly 30,000 citations and an h-index of over 75. His research has also been awarded six lasting impact “test-of-time” awards.