Interests
My site: https://jqyu.me/
My research interests encompass several key areas:
- Intelligent Transportation Systems (ITS): Within the realm of ITS, I focus on the application of cutting-edge deep learning techniques. My goal is to develop intelligent algorithms capable of optimizing traffic flow, enhancing safety, and reducing congestion. Furthermore, I work to integrate privacy-preserving computing methods into these systems to safeguard user data while harnessing the power of data-driven decision-making. This intersection of ITS and privacy computing holds immense promise for creating secure, efficient, and privacy-conscious transportation networks.
- Privacy-Preserving Computing: Privacy is a fundamental concern in today's interconnected world. In this context, I specialise in the development of secure and privacy-enhancing technologies. This includes research into advanced encryption techniques like homomorphic encryption and the implementation of federated learning approaches. My primary focus is to apply these methods in practical scenarios, particularly in the context of ITS, where sensitive data protection is paramount. By ensuring the confidentiality of personal information, we can unlock the full potential of data-driven transportation systems while respecting individuals' privacy rights.
- Deep Learning Techniques: My research extends to the ever-evolving field of deep learning. I am committed to advancing the capabilities of neural networks. A significant part of my work revolves around utilising deep learning to revolutionise transportation systems, including autonomous vehicles, predictive maintenance, and traffic prediction. Through innovative deep learning techniques, we can address critical challenges and transform the way transportation operates in the modern world.
Qualifications
- Doctor of Philosophy, The University of Hong Kong, 2015
- Bachelor of Engineering (Hons.), The University of Hong Kong, 2011
Career
- Lecturer, Department of Computer Science, University of York, 2023-
- Assistant Professor, Department of Computer Science and Engineering, Southern University of Science and Technology, 2018-2023
- Postdoctoral Research Fellow, Department of Electrical and Electronic Engineering, The University of Hong Kong, 2015-2018
Biography
James J.Q. Yu is a Lecturer at the Department of Computer Science, University of York, and an honorary assistant professor at the Department of Electrical and Electronic Engineering, the University of Hong Kong. Before that, he was an assistant professor at the Department of Computer Science and Engineering, Southern University of Science and Technology, Shenzhen, China from 2018 to 2023. He received the B.Eng. and Ph.D. degree in electrical and electronic engineering from the University of Hong Kong, Pokfulam, Hong Kong, in 2011 and 2015, respectively, where he was a post-doctoral fellow from 2015 to 2018. His general research interests are in smart city and privacy computing, deep learning, intelligent transportation systems, and smart energy systems. His work is now mainly on forecasting and decision making of future transportation systems and artificial intelligence techniques for industrial applications. He was listed in the World's Top 2% Scientists of from 2020 to 2022 by Stanford University, ranked at top 0.32% of all Artificial Intelligence scholars. He is an Editor of the IET Smart Cities journal and a Senior Member of IEEE.