T4: Emerging Technologies, 5G and Beyond: Task-oriented Co-design of Sensing, Communication, and Control for Cyber-Physical Systems

Co-organizer: Philip Zhao, University of Manchester, UK
Co-organizer: Daniele De Martini, University of Oxford, UK
Co-organizer: Emma Li, University of Glasgow, UK
Co-organizer: Yufeng Diao, University of Glasgow, UK

Abstract: This half-day tutorial focuses on task-oriented co-design of sensing, computing, and control for edge-enabled Cyber-Physical Systems (CPS) with a wide range of emerging applications in 5G and beyond, including connected vehicles, robotics, and Artificial Intelligence (AI). We will discuss the technical challenges and roadmap to achieve the seamless integration of sensing, communication and control within practical constraints. We will also demonstrate and share our latest research outcomes from the University of Manchester, Oxford Robotics Institute, and the University of Glasgow, including computer simulation and hardware prototyping. In addition, we will provide detailed instructions on how to design, implement, and test an integrated sensing, communication, and control system in the context of edge-intelligence assisted autonomous driving. We will further offer some co-design examples to tailor the system for different tasks. Our goal in this tutorial is to provide audiences a set of tools, technologies, and examples to address the technical challenges in edge enabled applications in 5G and beyond.

Co-organizer’s Bios:

Philip Zhao

Dr Philip Zhao is a Senior Lecturer at the Department of Computer Science, University of Manchester (UoM), UK. Prior to joining UoM in 2024, he was a Lecturer/Senior Lecturer at the University of Glasgow, UK, from 2018 to 2023. Dr Zhao is recognized as a Senior Member of IEEE and is also a member of IET. His areas of expertise lie in strategy and technology innovation. His research focuses on AI-driven cross-system design and optimization for various applications, including robotics, Cyber-Physical Systems (CPS), Internet of Things (IoT), communication networks, and computer vision. His project portfolio reflects a total funding of £3 million, with more than £800k secured as the Principal Investigator (PI). He has made significant contributions to academia with over 100 publications, including in prestigious journals such as JSAC, TCOM, TWC, JSTSP, and TSP, as well as top conferences like ICRA, IROS, INFOCOM, ICC, and Globecom. He won three best paper awards and received 2800+ citations in Google Scholar.

Daniele De Martini

Dr Daniele is a Departmental Lecturer in Mobile Robotics and co-leads with Professor Paul Newman the Mobile Robotics Group at the University of Oxford. He is also a College Lecturer in
Engineering Science at Pembroke College. Dr Daniele is interested in robust navigation and scene understanding — from odometry and localisation to detection and segmentation — enabling the
deployment of robots in challenging weather and scenarios. He is exploring techniques to improve robustness either by utilising inherently more robust sensors, focusing on FMCW scanning radar
technology, or enhancing the training of perception modules.

Emma Li

Dr Emma Li is a Senior Lecturer in Responsible & Interactive Artificial Intelligence at the School of Computing Science, a supervisor of the UKRI Centre for Doctor Training in Socially Intelligent
Artificial Agents (Social AI CDT), and an affiliated staff at School of Engineering. Before joining University of Glasgow, she was a senior lecturer at Northumbria University at Newcastle, UK.
She leads the Interactive and Trustworthy AI lab working on human-robot interaction and cyber security. Our research goal is to accelerate human-robot partnership into industry and society. She has successfully delivered 6 projects and published 50 peer reviewed papers. Her recent work on robot behaviour-based user authentication received a best workshop paper award in IEEE INFOCOM 2021. Her lab has access to the state-of-the-art industrial tele-robotic arm platform (e.g., Franka Emika and UR3e/UR5e Robots) and mobile robot platform (e.g., HUSKY and Jackal unmanned ground vehicles) at the University of Glasgow. She is interested in data-driven AI design and experiments in robotics systems for a variety of applications, e.g., social & health care, industry, service, etc.

Yufeng Diao

Mr. Yufeng Diao is a final-year PhD candidate in the School of Computing Science at the University of Glasgow, U.K. His research interests include task-oriented communication, task-oriented crosssystem design, variational information bottleneck, and edge intelligence. He was awarded student conferenceship at the 38th Annual Computer Security Applications Conference (ACSAC). He is a Graduate Student Member of IEEE. Mr. Diao has made significant contributions to academia, with publications in prestigious journals (e.g., JSAC and Journal of Dentistry) and top conferences (e.g., INFOCOM and ACSAC).