Rich Turner

Professor at University of Cambridge

I’m Rich Turner, a Professor of Machine Learning in the Machine Learning Group at the University of Cambridge and a Research Lead, AI for Weather Prediction, at the Alan Turing Institute.

I am the Cambridge Lead for the EPSRC Probabilistic AI Hub.

My previous roles include Visiting Researcher at Microsoft Research in the AI4Science and AI teams, Co-Director of the UKRI Centre for Doctoral Training in the Application of Artificial Intelligence to the study of Environmental Risks (AI4ER CDT), and Course Director of the Machine Learning and Machine Intelligence MPhil programme. I have received over £30 million of funding as a Principal or Co-Investigator. I’ve been awarded the Cambridge Students’ Union Teaching Award for Lecturing.

My current research interests include:

  • Probabilistic Machine Learning Fundamentals (including generative models and uncertainty-aware approaches)
  • Environmental Prediction (especially for weather, earth systems, and climate prediction)
  • Spatio-temporal Modelling (especially using a fusion of large-scale deep learning and probabilistic modelling for scientific applications)

Below you’ll find information about my group.

You can stay up to date with my most recent research on Google Scholar or by following me on LinkedIn or the Cambridge MLG twitter account.

Directions to my office are here.

Selected work

Papers

Tutorials

Blog posts

Recent news

Apply

If you are interested in applying to my group in Cambridge, please check the guide on the CBL Machine Learning Group website. You can also reach out to me or one of my students.

If you are interested in collaborating, please get in touch at ret26 at cam.ac.uk.

Please note that I very rarely take internship students and have more requests for these than I can reply to.

Group members

Current

Former

PhD

Marcin Tomczak

Thesis: Improved Sampling and Variational Inference Methods for Neural Networks

Next: Quantitative researcher at G-Research

2019
2024
Postdoc

Emile Mathieu

Next: Machine learning researcher at Xaira Therapeutics

2022
2024
Postdoc

Vincent Fortuin

Next: Principal investigator at Helmholtz AI

2022
2023
Postdoc

Massimiliano Patacchiola

Next: Research engineer at Tools for Humanity

2021
2023
Visiting industrial fellow

Lachlan Thorpe

Next: Senior machine learning software engineer at Hawk-Eye Innovations Ltd

2022
2023
PhD

Elre Oldewage

Thesis: Advances in Meta-Learning, Robustness, and Second-Order Optimisation in Deep Learning

Next: Application engineer at MathWorks

2018
2023
PhD

Will Tebbutt

Thesis: Advances in Software and Spatio-Temporal Modelling with Gaussian Processes

Next: Postdoctoral researcher at the Alan Turing Institute and University of Cambridge

2017
2022
PhD

Wessel Bruinsma

Thesis: Convolutional Conditional Neural Processes

Next: Senior researcher at Microsoft Research

2018
2022
PhD

Siddarth Swaroop

Thesis: Probabilistic Continual Learning using Neural Networks

Next: Postdoctoral fellow at Harvard University

2017
2022
PhD

Jonathan Gordon

Thesis: Advances in Probabilistic Meta-Learning and the Neural Process Family

Next: Research scientist at OpenAI

2018
2022
PhD

James Requiema

Thesis: The Neural Processes Family: Translation Equivariance and Output Dependencies

Next: Postdoctoral fellow at Vector Institute and University of Toronto

2016
2022
PhD

Andrew Foong

Thesis: Approximate Inference in Bayesian Neural Networks and Translation Equivariant Neural Processes

Next: Senior researcher at Microsoft Research

2018
2022
PhD

Shixiang Gu

Thesis: Sample-Efficient Deep Reinforcement Learning for Continuous Control

Next: Research scientist at Google Brain

2014
2019
Research assistant

Michael Hutchinson

Next: PhD student at the University of Oxford

2019
2019
PhD

Yingzhen Li

Thesis: Approximate Inference: New Visions

Next: Researcher at Microsoft Research

2013
2018
PhD

Matejo Rojas-Carulla

Thesis: Learning Transferable Representations

Next: Research scientist at Facebook AI Research

2014
2018
PhD

Mark Rowland

Thesis: Structure in Machine Learning: Graphical Models and Monte Carlo Methods

Next: Research scientist at DeepMind

2014
2018
Postdoc

Cuong Nguyen

Next: Assistant professor in Statistics at Durham University

2016
2018
Postdoctoral fellow

Arno Solin

Next: Assistant professor at Aalto University, Finland

2017
2018
PhD

Thang Bui

Thesis: Efficient Deterministic Approximate Bayesian Inference for Gaussian Process models

Next: Lecturer in Machine Learning and Data Science at the University of Sydney

2013
2017
PhD

Alexandre Navarro

Thesis: Probabilistic Machine Learning for Circular Statistics: Models and inference using the Multivariate Generalised von Mises distribution

Next: Senior research scientist at AstraZeneca

2013
2017
Postdoc

Filipe Tobar

Next: Senior lecturer in Machine Learning at Imperial College London

2014
2015
Research assistant

Rosy Southwell

Next: PhD student at University College London

2013
2014