Edwin Fong

edwin_fong

Former position

Doctoral Student

Partner Institution

Bio

Edwin is a former DPhil student at the Department of Statistics, University of Oxford under the supervision of Professor Chris Holmes. He previously completed an MEng at the University of Cambridge, specialising in information engineering and machine learning. Through this, he developed an interest for the mathematics behind machine learning methods, prompting his switch of focus to statistics.  Beyond his interest in methodology, he is motivated by the application of statistics in healthcare and medical research.

Research interests

Within many scientific settings, there is the need to make quantitative statements of uncertainty to inform decision-making, and Bayesian inference offers a strong framework for achieving this. However, as datasets grow in size and complexity, the challenges of scalability and model misspecification become serious for the Bayesian. Edwin is particularly interested in the foundations of Bayesian inference, and is investigating Bayesian nonparametric methodologies that are flexible, scalable and robust to model error.

Achievements and awards

Edwin is the recipient of the 2022 Savage Award from the International Society for Bayesian Analysis for his PhD thesis "The predictive view of Bayesian inference".