معرفی
Chris Oates leads a research team in Computational Statistics and Probabilistic Machine Learning at Newcastle University's School of Mathematics, Statistics and Physics. He serves on the Programme Committee of the ICMS (2025–2028) and as an Associate Editor of the SIAM/ASA Journal of Uncertainty Quantification (2025–2027). His work focuses on advancing Bayesian computation, Monte Carlo methods, and uncertainty quantification, supported by grants such as a £0.8M EPSRC award (2022–2026) for Stein Discrepancy methodologies.
Research interests include robust Bayesian inference for intractable likelihoods, optimal thinning of MCMC outputs, and reinforcement learning for adaptive sampling. His team develops software like Stein Thinning (stein-thinning.org) and has published breakthroughs in probabilistic Richardson extrapolation and prediction-centric uncertainty quantification using MMD.
Awarded the Guy Medal in Bronze (2024) and a Leverhulme Prize (2024), he has advised over a dozen PhD students and postdocs, including co-supervised projects at King’s College London and Imperial College. Current funding includes a Heilbronn Institute grant for next-generation extrapolation methods and a Turing Fellowship (2024–2026).
Labs/Teams: Active in the Alan Turing Institute collaboration network, leading a multidisciplinary group spanning computational statistics, machine learning, and interdisciplinary applications in geospatial systems and cardiovascular data science.
