Keynote Speakers

Abstract:
Worldwide, the population is aging due to increasing life expectancy and decreasing fertility. The significant growth in older population presents many challenges to health and aged care services. Over the past two decades, the Internet of Things (IoT) has gained significant momentum and is widely regarded as an important technology to change the world in the coming decade. Indeed, IoT will play a critical role to improve productivity, operational effectiveness, decision making, and to identify new business service models for social and economic opportunities. Indeed, with the development of low-cost, unobtrusive IoT sensors, along with data analytics and artificial intelligence (AI) technologies, there is now a significant opportunity to improve the wellbeing and quality of life particularly of our older population. In this talk, we will overview some related research projects and also discuss several research directions.

Michael Sheng’s Bio:
Michael Sheng is a full Professor and Head of School of Computing at Macquarie University, Sydney, Australia. Before moving to Macquarie University, he spent 10 years at School of Computer Science, the University of Adelaide. Michael Sheng’s research interests include the Internet of Things (IoT), service computing, big data analytics, machine learning, and Web technologies. He is ranked by Microsoft Academic as one of the Most Impactful Authors in Services Computing (ranked Top 5 All Time) and in Web of Things (ranked Top 20 All Time). Michael Sheng is the recipient of AMiner Most Influential Scholar in IoT (2018), ARC (Australian Research Council) Future Fellowship (2014), Chris Wallace Award for Outstanding Research Contribution (2012), and Microsoft Research Fellowship (2003). He is the Vice Chair of the Executive Committee of the IEEE Technical Community on Services Computing (IEEE TCSVC), the Associate Director of Macquarie University Smart Green Cities Research Center, and a member of the ACS (Australian Computer Society) Technical Advisory Board on IoT.

Abstract:
This lecture discusses the problem of behavior understanding of intelligent agents. From the perspective of machine cognition, how to make the machine understand the behavior? Introduce the work of human behavior knowledge engine and behavior semantic unification under Poincaré space. From the perspective of neurocognition, what is the inner relationship between machine semantic understanding and brain neurocognition? Introduce how to explain the intrinsic relationship between visual behavior understanding and brain nerves, and establish a stable mapping model. From the perspective of embodied cognition, how to make the robot have the first-person behavior ability? Introduce the proposed PIE (perception-imagination-execution) scheme, in which the representative work grassNet reaches the human level for the first time in grasping unknown objects.

Cewu Lu’s Bio:
Cewu Lu is a professor of Shanghai Jiao Tong University. In 2016, he was selected as the National "1000 Youth Talents Plan". In 2018, he was selected as 35 Innovators Under 35 (MIT TR35) by MIT Technology Review. In 2019, he was awarded Qiu Shi Outstanding Young Scholar. In 2020, he was awarded the Special Prize of Shanghai Science and Technology Progress Award (ranked third). In 2021, he won the title of Highly Cited Scholar in China. In 2022, he was awarded one of the best papers in IROS (6/3579). he, as the corresponding author or the first author, has published 100 papers in high-level journals and conferences. And he Served as reviewer for Sicence main issue, Nature sub-journal, Cell sub-journal and other journals, area chair of NeurIPS, CVPR, ICCV, ECCV, IROS, ICRA. His research interests fall mainly in Computer Vision and Robot Learning.