Edge computing provides a powerful way to rapidly analyze data and process tasks at the edge of the network, closer to the end-user. Edge AI extends edge computing to enable AI on edge devices to make instantaneous intelligent decisions. In this talk, I will describe the vision of future Edge AI, called Ubiquitous AI, empowered by collaborative edge computing (CEC), which is a new-generation scalable edge computing infrastructure. With the computing power shared by collaborative edge nodes, edge AI models can be trained and seamlessly deployed jointly by the edge nodes that can be geographically distributed across a wide area. I will highlight the architecture and framework of CEC and how it enables ubiquitous AI demanded by advanced smart city applications like autonomous driving, industry 4.0 and metaverse.
Professor Cao’s research interests include edge computing and distributed systems, wireless sensing and networking, big data and AI. He published 6 co-authored and over 500 papers in major international journals and conference proceedings. He also obtained 13 patents. He received many awards for his outstanding research achievements. Professor Cao served the Chair of the Technical Committee on Distributed Computing of IEEE Computer Society 2012-2014. He is a member of Academia Europaea, a fellow of HK Academy of Engineering Sciences, a fellow of IEEE, a fellow of CCF and a distinguished member of ACM.
Clean water and clean air are vital for public health. This project focuses on developing high-efficiency and environmentally sustainable filters for removing harmful air/water pollutants. The team has developed novel architectures and functionalities for the filters to achieve high permeance, high removal efficiency, and excellent reusability.
