Professor Anton van den Hengel

Anton van den Hengel is a Director of Applied Science at Amazon, the Director of the Centre for Augmented Reasoning at the Australian Institute for Machine Learning (AIML), a Professor of Computer Science at the University of Adelaide, a Chief Investigator of the NHMRC Centre of Research Excellence on Healthy Housing, and a Fellow of the Australian Academy of Technology and Engineering. The Centre for Augmented Reasoning (CAR), established in 2021, represents a $20m investment by the Australian Government in AI research. Prof van den Hengel was also the founder of AIML, Australia’s largest machine learning research group. Professor van den Hengel has been a CI on over $80m in research funding from sources, including Google, Facebook, Canon, BHP Billiton, and the ARC.

Prof van den Hengel has won several awards, including the 2021 Australasian AI Outstanding Service Award, the Pearcey Foundation Entrepreneur Award, the SA Science Excellence Award for Research Collaboration, and the CVPR Best Paper prize in 2010. According to Google Scholar, he has authored over 400 publications, has an h-index over 70. He has had 8 patents commercialised, formed 5 startups, and had a medical technology achieve first-in-class FDA approval. Current research interests include deep learning, vision and language problems, image-based modelling, and weekly supervised learning.

Akihiko Sugiyama

Akihiko Sugiyama (a.k.a. Ken Sugiyama), affiliated with Yahoo! JAPAN Research, has been engaged in a wide variety of research projects for consumer and network-system products through signal processing such as audio coding and interference/noise control. Prior to Yahoo Japan, he had a long career at NEC Central Research Laboratories as a research engineer. His team at NEC developed the world’s first all solid-state portable audio player, the Silicon Audio, in 1994. He has developed over 300 new contacts in the world-leading companies in two years for PoC (proof-of-concept) evaluations. He was representing Japan for the MPEG-1 through MPEG-4 standardization. He has been teaching at universities for 20 years and supervised 75 internship students.

He served as the Chair of Audio and Acoustic Signal Processing Technical Committee, Signal Processing Society (SPS), as an Associate Editor of IEEE Transactions on Signal Processing, as the Secretary and a Member at Large to the SPS Conference Board, as a member of the SPS Awards Board, as the Chair of SPS Japan Chapter, and a Technical Program Chair for ICASSP2012. Currently, he serves as a member of the IEEE Fellow Committee and the IEEE James Clerk Maxwell Medal Committee. He has contributed to 17 chapters of books and is the sole inventor or a co-inventor of 217 registered patents in the field of signal processing in Japan, US, EPC, Canada, Australia, Korea, Taiwan, and Brazil as well as 6 registered trademarks. He received 21 awards including the 2002 IEICE Best Paper Award, the 2006 and 2018 IEICE Achievement Award, the 2013 Ichimura Industry Award, and the 2021 IEICE Distinguished Achievement and Contribution Award. He has delivered 174 invited talks in 87 cities of 31 countries. He is a past SPS Distinguished Industry Speaker, a Renowned Distinguished Speaker (The Rock Star) for Consumer Technology Society (CTS) and a past Distinguished Lecturer for SPS and CTS. He is a Fellow of IEEE, a Fellow and Honorary Member of IEICE and a member of APSIPA.

Mar Gonzalez Franco

Dr. Mar Gonzalez-Franco is a Computer Scientist and Neuroscientist at Google working on a new generation of Immersive technologies. With a background in real-time systems in her research she tries to build better interactions for immersive technologies using different disciplines: Virtual Reality, Augmented Reality, Avatars, computer graphics, computer vision and haptics. All while studying human behavior, perception and neuroscience.

Priorly, she was Principal Researcher in the EPIC (Extended Perception Interaction and Cognition) team at Microsoft Research.

Dr. Gonzalez-Franco holds a BSc in Computer Science (URL, Barcelona) and MSc in Biomedical Engineering (Universitat de Barcelona and Tsinghua University). She earned her Ph.D. in Immersive Virtual Reality and Clinical Psychology under the supervision of Prof. Mel Slater at the EVENT-Lab, affiliated as a visiting student at the Massachusetts Institute of Technology, MediaLab. She completed her postdoctoral studies at University College London. Dr. Gonzalez-Franco is an expert advisor to governments (UN, US NSF, Canada NSERC, European Commission), as well as prolific scientist with publications and service as program committee, chair, and reviewed in top venues (IEEE & ACM conferences and transactions, Nature Publishing group, Science Robotics etc). She is often invited to write commentaries on her work for Scientific American and presents keynotes and interviews with international media including Bloomberg or The Royal Society. She was awarded the prestigious IEEE VR New researcher award in 2022. And since 2020, she is the Ethics and Diversity Chair of IEEE VGTC.

Apart from her prolific scientific output and academic recognitions, Dr. Gonzalez-Franco's work has also transferred to products used on a daily basis by many around the world, such as the Avatars and Together mode in Microsoft Teams and Microsoft Soundscape, as well as features on Hololens and Xbox. The release of Avatars in Teams was awarded Times invention of the year in 2022. And it is to date the largest deployment of avatars in any platform for productivity, available to the 270 million users of MS Teams.

Learn more about this speaker:

http://margonzalezfranco.GitHub.io

On the value of memory, and the benefits of forgetting

Deep learning has become the default method for solving most ML problems but has some significant limitations. These include the inherent difficulty in editing, updating, and controlling deep models. One of the causes of this problem is the fact that deep models store information implicitly in the values of multiple weights. This talk will cover two approaches to solving this problem by augmenting a deep model with explicit information storage. The resulting augmented models are able to be updated on the fly, at inference time, but also outperform standard deep learning architectures when this is not required. The approach also points towards methods that might enable late-binding in deep learning, which would broaden their applicability significantly.

Personal Information Devices: Portable to wearable, Stand-alone to connected, Players to sensors.

This talk presents a history of personal information devices. The origin is an audio player dated back to the 1990s which was born at an intersection of audio coding algorithms to provide sufficient subjective audio quality and a sufficient memory size on a single chip. LSI technology was indispensable to its birth which had a revolutionary impact on the hardware business. The audio-only device was naturally extended to include video signals to cover multimedia applications commonly encountered today in our daily life. Integration with a mobile phone brought us continuous extensions to wearables, connected operations, and sensing functions.

The Power of Extended Reality in the AI era.

Extended Realities aim to blend further our digital and analog worlds, these are immersive technologies that will be deeply connected to human perception and behaviour with their environment. Exploring them all together: the technology and the humans, will help to highlighting which things are particular to this medium. In this keynote we present a body of research done across the space of immersive technologies, from avatars to haptics, to authoring tools. This will be the starting point to discuss why XR is so interesting, and how it compares or interface to other mediums. All to find what is impossible to do outside of immersive technology, and how will AI impact this technology.