Department of Engineering / Profiles / Dr Richard E. Turner

Department of Engineering

Dr Richard E. Turner

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Richard E. Turner

Reader in Machine Learning

Academic Division: Information Engineering

Research group: Computational and Biological Learning

Telephone: +44 1223 7 48517

Email: ret26@eng.cam.ac.uk

Personal website

Publications


Research interests

Dr. Turner's research spans the following areas:

  1. machine learning which provides a theoretical framework for learning and making inferences from data in order to make decisions.
  2. computer perception and cognition which builds automatic systems for processing and understanding images, sounds and videos
  3. statistical signal processing which uses techniques from statistics and machine learning to develop new signal processing methods
  4. machine learning for climate science which employs advanced machine learning methods to improve predictions for climate modelling and forecasting to facilitate decision making

Particular current focusses are: deep probabilistic learning, human-like learning, continual learning, k-shot learning, active learning, transfer learning, reinforcement learning, concept learning, probabilistic models, Bayesian statistics, Bayesian neural networks, Gaussian processes, spatio-temporal modelling, approximate inference, scalable and distributed inference, Monte Carlo methods, variational methods, expectation propagation, and Bayesian optimisation. We are also interested in the connection between machine learning and computation in the brain.

Biography

Dr. Turner is a Reader in Machine Learning in the Department of Engineering at the University of Cambridge and a Visiting Researcher at Microsoft Research Cambridge. Dr. Turner is Course Director of the Machine Learning and Machine Intelligence MPhil programme. He is also Co-Director of the UKRI Centre for Doctoral Training in the Application of Artificial Intelligence to the study of Environmental Risks (AI4ER CDT). Over the last two years his work has been presented in oral presentations at top machine learning conferences including AAAI, AIStats, ICLR, ICML and NeurIPS and he has given keynote lectures and tutorials at the Machine Learning and Signal Processing Summer School, the International Conference on Machine Learning, Optimization & Data Science, and the Machine Learning Summer School. He has been the lead supervisor for 13 PhD students (6 now graduated) and three RAs. He has received over £5M of industrial funding from Microsoft, Toyota, Google, DeepMind, Amazon, and Improbable and over £9M of funding from the EPSRC. Dr. Turner is on the Steering Committee for the Cambridge Centre for Data Driven Discovery (C2D3). He has been awarded the Cambridge Students' Union Teaching Award for Lecturing. His work has featured on BBC Radio 5 Live’s The Naked Scientist, BBC World Service’s Click and in Wired Magazine.