Welcome! I am a Lecturer (Assistant Professor) in Machine learning and Data Science in the Department of Computer Science, University of Bath. I also hold a visiting research scientist position in the Cavendish Laboratory, University of Cambridge.
Prior to joining Bath, I worked primarily as a Research Associate in the Cavendish Laboratory supervised by Prof. Mike Hobson and jointly as a Research Scientist in the Shell Technology Centre Amsterdam led by Chief Scientist of Computation and Data Science Prof. Detlef Hohl, working on statistical machine learning R&D for quantitative modelling and uncertainty quantification with applications in the oil/gas industry.
Research interests & expertise
- Bayesian inference and decision making
- Statistical machine learning and deep learning
- Probabilistic sampling and Monte Carlo numerical methods
- Statistical signal processing and data analytics
- Interdiciplinary applications using the above methods
I completed my Ph.D. in the Signal Processing and Communications Laboratory at Cambridge University in 2015. My Ph.D. research was in the area of Bayesian statistics and signal processing (supported by Man Group plc) under the supervision of Prof. Simon Godsill and the co-supervision of Prof. Simo Särkkä. Prior to that, I received my M.Eng. degree (research-track) from McGill University, Canada in 2011. I was supervised by Prof. Mark Coates and was also guided by Prof. Mike Rabbat in the Computer Networks Laboratory. Before that, I obtained my B.Eng. degree from Beijing University of Posts and Telecommunications, China in 2009. I completed my undergraduate final year project (supported by Santander Group) under the supervision of Prof. José Fernán Martínez at Universidad Politécnica de Madrid, Spain.
I grew up in a beautiful small town Xiamen (Amoy), which is an island in Southeast China facing Taiwan Strait of the Pacific Ocean. It is part of a broader region speaking local dialect Hokkien, and famous for its seafood dishes (e.g. Oyster Omelette and Fish Ball).
Associate Editor (2019 - present), IET Signal Processing Journal.
Spring 2020: CM50268 Bayesian Machine Learning
Autumn 2019: CM50264 Machine Learning 1