I am a Lecturer in Artificial Intelligence in the Department of Computer Science and a member of the Nature Inspired Computing and Engineering (NICE) Group. Prior to joining Surrey, I was a Postdoctoral Research Assistant in Machine Learning working with Steve Roberts in the Machine Learning Research Group, University of Oxford. I was also a Junior Research Fellow at Wolfson College, University of Oxford. I completed my Ph.D. in electrical engineering with Mark Coates at McGill University in Montréal, Canada.
My research interests are in the areas of machine learning and statistical signal processing. I have a particular interest in designing Bayesian and Monte Carlo inference techniques effective in high-dimensional spaces. I have applied machine learning and signal processing techniques to diverse problem domains including environmental acoustic detection, device-free target tracking in sensor networks, and microwave breast cancer detection.
Areas of specialism
I am actively looking for PhD students with a strong interest and background in deep learning and Bayesian inference. One fully funded PhD studentship (UK/EU tuition + stipend for 3 years) is available on the topic of "Uncertainty Quantification for Robust AI through Optimal Transport". Please contact me if you are interested in working with me. We support China Scholarship Council (CSC) scholarship applications with tuition fee waiver.
In the media
I am interested in foundational machine learning topics motivated by applications aiming to improve human life and environment. I am currently working on improving the ability of deep neural networks to quantify uncertainty in their predictions, which can benefit vast data science domains, from disease diagnostics to autonomous driving. My work on Monte Carlo sampling, optimal transport theory, Bayesian classifier fusion has found applications in cancer detection, robotics, target tracking, and environment sensing. My research is impact-driven and received media coverage from MIT Technology Review, Digital Trends, New Scientist, The Guardian, BBC, among other venues.
Building an AI-powered system with the capability in recognising normal anatomical structures and differentiate from subtle abnormalities in digitised dental radiographic images.
Postgraduate research supervision
PhD students (Principal Supervisor):
Xiongjie Chen (2019 - )
Hao Wen (2019 - )
Camellia Ruoqing Yin (2020 - )
Completed postgraduate research projects I have supervised
Undergraduate student researcher:
Georgios Papagiannis (2019 - 2020; now MPhil at the University of Cambridge)
- COMM054: Data Science Principles and Practices (2019 - )
- COM1033: Foundations of Computing II (2018 - )
- Year 1 (undergraduate) Coordinator and Personal Tutor (2018 - )
- Industry Placement Visiting Tutor (2018 - )
- Departmental Seminar Organiser (2018 - 2019)