Sustainability and Machine Learning Group

Research group

University College London

We are a research group at UCL’s Centre for Artificial Intelligence.

Our research expertise includes:

  • data-efficient machine learning and probabilistic modeling
  • autonomous decision making and recommender systems
  • responsible AI and AI safety

We also work on applications related to social/environmental sustainability, climate and nuclear fusion.

If you are interested in joining the team, please check out our openings.

SML Group in November 2023
SML Group in November 2023

Meet the Team

Principal Investigators

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Marc Deisenroth

Google DeepMind Chair of Machine Learning and Artificial Intelligence

Machine learning, Gaussian processes, Reinforcement learning, Robotics, Meta learning

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Maria Perez-Ortiz

Associate Professor

Responsible AI, AI for sustainability, Recommender systems, Hybrid intelligence, Simulation intelligence

Administrators

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Alice Winters

Administrator

Research Fellows

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Daniel Giles

Senior Research Fellow

Tsunami modeling, HPC, Gaussian processes

PhD Students

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Sicelukwanda Zwane

PhD Student

Machine learning, Robotics, Transfer Learning, Reinforcement Learning

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Daniel Augusto de Souza

PhD Student

Machine learning, Gaussian processes

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Yicheng Luo

PhD Student

Meta-learning, Probabilistic Programming, Reinforcement Learning, Deep Generative Models

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Jackie Kay

PhD Student

Sociotechnical AI, Robotics

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Jake Cunningham

PhD Student

Machine learning, Gaussian processes, Earth systems modelling

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Samuel Cohen

PhD Student

Machine learning, Optimal transport, Gaussian processes

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Jacob Menick

PhD Student

Machine learning, Generative models, Large-scale deep learning, Variational inference, Information theory, Sparsity

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James Rudd-Jones

PhD Student

Sustainable policies, socio-environmental AI

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Mathieu Alain

PhD Student

Machine learning, Graph neural networks, Diffusion models, PAC-Bayes

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Noah Siegel

PhD Student

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Vignesh Gopakumar

PhD Student

Machine learning, Nuclear fusion, Bayesian optimization, Neural operators

Project Students

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Clare Grogan

MSc Project Student

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Nathan D'Souza

UG Project Student

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Sree Sanakkayala

UG Project Student

Visitors

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Chong Chen

Associate Professor @ China University of Petroleum-Beijing

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Dongmei Mo

Post-doc @ The Hong Kong Polytechnic University

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Florian Pfaff

Post-doc @ Karlsruhe Institute of Technology

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Kenta Hoshino

Assistant Professor @ Kyoto University

Affiliates

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Giovanni Franzese

PhD Student @ TU Delft and ELLIS Exchange Student

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Yasemin Bekiroğlu

Senior Research Fellow (08/2021 - 07/2023)

Machine learning, Robotics

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So Takao

Senior Research Fellow (11/2020 - 07/2023)

Machine learning, Climate science, Fluid mechanics, Geometric mechanics

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Rendani Mbuvha

DeepMind Academic Research Fellow in AI @ QMUL

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Christina Winkler

PhD Student @ TU Munich

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Fabian Paischer

PhD Student @ JKU Linz and ELLIS Exchange Student

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Mirgahney H. Mohamed

PhD Student

Computer vision, Uncertainty estimation

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Oscar Key

PhD Student

Probabilistic modeling, Approximate inference, Machine learning, Climate science

Alumni

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Alexander Terenin

PhD (10/2018-11/2021)

Machine learning, Bayesian theory, Geometric machine learning

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Yasemin Bekiroğlu

Senior Research Fellow (08/2021 - 07/2023)

Machine learning, Robotics

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So Takao

Senior Research Fellow (11/2020 - 07/2023)

Machine learning, Climate science, Fluid mechanics, Geometric mechanics

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Sanket Kamthe

PhD (10/2016-03/2021)

Machine learning, Reinforcement learning, Optimal control, Copulas

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Mihaela Rosca

PhD Student (03/2020-05/2023)

Generative models, Optimization in deep learning, Reinforcement learning

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Hugh Salimbeni

PhD (10/2015-10/2019)

Machine learning, Deep probabilistic models, Approximate inference

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Steindór Sæmundsson

PhD (11/2016-11/2021)

Machine learning, Gaussian processes, Meta learning, Structural priors, Variational inference

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K. S. Sesh Kumar

Research Associate

Machine learning, Discrete optimization, Differential privacy, Submodularity

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Riccardo Moriconi

PhD (10/2016-02/2021)

Machine learning, Gaussian processes, Bayesian optimization

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Janith Petangoda

PhD Student (10/2017-07/2022)

Machine learning, Meta learning, Differential geometry, Reinforcement learning

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James Wilson

PhD Student (10/2017-08/2022)

Machine learning, Gaussian processes, Bayesian optimization, Practical approximate inference

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Simon Olofsson

PhD (06/2016-03/2020)

Machine learning, Bayesian optimization, Mechanistic models, Model discrimination

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Benjamin Chamberlain

PhD (10/2014-08/2018)

Machine learning, Community detection, Representation of graphs, Hyperbolic embeddings

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Sophie Ostler

Administrator (08/2021-08/2022)

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