I am a PhD student in Mathematics and Statistics at the University of Edinburgh, affiliated with the School of Mathematics. My research focuses on high-dimensional Bayesian Machine Learning methodologies. I am fortunate to be supervised by Dr. Torben Sell and Dr. Cecilia Balocchi.

My work spans both the applied and theoretical sides of Bayesian Machine learning. For applications, I am developing a Bayesian clustering method for satellite image segmentation that incorporates spatial correlation and informative priors, aiming to deliver a general-purpose, robust, and stable segmentation approach for high-dimensional images under distribution shifts.

From theoretical side, I mainly work on Bayesian Deep learning, where I study the posterior concentration rate under Bayesian Deep learning settings. The research aims to provide a theoretical justification for the optimal minimax concentration rate with a well-designed network under simple priors (e.g., Gaussian priors) in a computationally efficient framework.

Before my doctoral studies, I obtained my Master’s degree from Queen Mary University of London (U.K) and the Bachelor’s degree from Hanoi National University of Education (Vietnam), both in Mathematics.

News!!

• June, 2026: My first PhD paper Scalable Bayesian Spatial Mixture Modelling for Remote Sensing Image Segmentation is now available on arXiv.
• May, 2026: I was awarded the New Researcher Travel Award by ISBA.
• March, 2026: I will present my research work at the ISBA World Meeting and the Bayesian Young Statistician Meeting (BAYSM), Japan (June 2026).
• March, 2026: I was awarded the Early Career Research Travel Grant by London Mathematical Society.
• May, 2025: Winning Team of the International Centre for Mathematics Sciences Modelling Camp 2025, with the challenge from the Trainline company.

Contacts

Email: You can email me at B.K.Nguyen@sms.ed.ac.uk

My office: James Clerk Maxwell Building,
King’s Building Campus, University of Edinburgh
Edinburgh
EH9 3FD
United Kingdom