Tom Rainforth has been awarded the title of Professor of Statistics and, as of 1 September 2026, is also a Fellow of Jesus College.
He leads the RainML Research Lab, currently comprising four postdocs and twelve doctoral students, and is principal investigator on the ERC Starting Grant Data-Driven Algorithms for Data Acquisition, running until February 2029. His research spans optimal experimental design and probabilistic machine learning, with particular interests in Bayesian experimental design, active learning, uncertainty quantification, and large language models.
Tom has been part of the Department since 2017, initially joining as a postdoc in the group of Professor Yee Whye Teh, before starting to lead his own group in 2019, and then taking up his Associate Professor role in September 2024. Prior to this he completed his DPhil at Oxford in the Engineering Science Department under the supervision of Frank Wood and Maike Osborne.
What does a statistician do for the England football team?
From squad selection to modelling how footballs behave at altitude, statistician Matt Penn explains how data is helping shape the modern game, and why coaches will always matter more than the numbers.
New evidence suggests vast hidden magma systems inside Mars
Researchers from the Departments of Earth Science and Statistics have found evidence that Mars once hosted enormous, Earth-like magmatic systems deep below its surface – even though the planet lacks the plate tectonics long considered essential for this kind of geological complexity. The findings open up new possibilities for how rocky planets become habitable.
Finding a needle in the genomic haystack: Targeting rare genes using statistical outliers
In statistical modelling, extreme outliers are often written off as 'noise'. But a new study by researchers from Oxford's Department of Statistics and Big Data Institute published this week in The American Journal of Human Genetics reverses that principle, using these outliers as the basis of a targeting system for locating rare, high-impact genetic mutations.