The supervisors with research interests in ML methods, architectures, and deployment are listed below. Amir Vaxman My Website Reader in Graphics, Simulation and Visual ComputingResearchgeometry processing, discrete differential geometry, focusing on directional-field design, unconventional meshes, constrained shape spaces, architectural geometry, and medical applications Amos Storkey My Website Professor and Personal Chair of Machine Learning & Artificial IntelligenceResearchmachine learning methods, generative models and generative AI, machine learning and deep learning methodology, model understanding and efficiency Antonio Attili My Website Lecturer in Computational Reactive FlowsResearchTurbulence and combustion, soot formation in flames, aerosols, combustion instabilities, rocket propulsion, numerical methods, and massively parallel computing. Big-data analysis and applying machine learning and generative AI to fluid mechanics Antonio Vergari My Website Reader in Machine Learning SystemsResearchefficient inference with guarantees, complex probabilistic queries, automating probabilistic Machine Learning Watch an Interview with Antonio Vergari Changjian Li My Website Lecturer in Graphics, Simulation and Visual ComputingResearch3D Shape Creation and Analysis, applications in sketch-based modeling, shape reconstruction and analysis from point clouds, and medical image processing and modeling Elliot Crowley My Website Senior Lecturer in Electronics and Electrical EngineeringResearchsimplifying machine learning, AutoML (neural architecture search), efficient network training, low-resource deep learning, engineering applications of machine learning Fengxiang He My Website Lecturer in AI Driven Business Informatics and Financial ComResearchtrustworthy AI, deep learning theory and explainability, theory of decentralised learning, privacy in machine learning, symmetry in machine learning, learning theory in game-theoretical problems, and their applications in economics Hakan Bilen My Website ReaderResearchcomputer vision He Sun My Website ReaderResearchalgorithmic spectral graph theory, unsupervised learning, computational geometry, and randomised algorithms Henry Gouk My Website Lecturer in Machine LearningResearchartificial intelligence engineering Laura Sevilla My Website ReaderResearchvisual world in motion Michael Gutmann My Website Senior Lecturer in Machine LearningResearchmethods for (Bayesian) inference and design Nikolay Malkin My Website Chancellor's Fellow in AI and Data ScienceResearchdeep-learning-based reasoning (Machine learning for generative models, NLP and reasoning in language, computer vision) Oisin Mac Aodha My Website Reader in Machine LearningResearch(currently) computer vision and machine learning, with an specific emphasis on 3D understanding, human-in-the-loop methods, and AI for conservation and biodiversity monitoring Watch an Interview with Oisin Mac Aodha Steven McDonagh My Website Senior Lecturer in AI and Computer Vision for HealthResearchcomputer vision, machine learning and medical image analysis. multi-modal, multi-task learning and medical imaging applications Timothy Hospedales My Website Professor in Artificial IntelligenceResearchefficient and robust AI, meta-learning, lifelong transfer-learning in both probabilistic and deep learning contexts Viacheslav Borovitskiy My Website Lecturer in Machine LearningResearchgeometric learning, uncertainty quantification Watch an Interview with Viacheslav Borovitskiy Victor Elvira My Website Professor and Personal Chair in Statistics and Data ScienceResearchcomputational statistics, statistical signal processing, probabilistic machine learning, Monte Carlo methods, importance sampling methodology - including sequential Monte Carlo (particle filtering), Bayesian inference in static and dynamical models, statistical modelling and inference in population ecology, signal processing for biomedical applications and wireless communications, (currently on) forecasting climate tipping points probabilistically Wenda Li My Website Lecturer in Hybrid AIResearchneuro-symbolic reasoning, AI for math, machine learning for theorem proving, mechanised mathematics This article was published on 2025-10-28
