Prof Theo Damoulas

简介

I am a Professor in Machine Learning and Statistics with a joint appointment in Computer Science and Statistics. I am the head of the Foundations in AI and ML (FAM) Division in CS and a Turing AI Fellow (2021-2026) having received the UK Research and Innovation (UKRI) Turing AI Acceleration FellowshipLink opens in a new window in order to lead research on setting the Machine Learning Foundations of Digital Twins. I am an ELLIS member and also affiliated with New York University as a Visiting Exchange Professor at the Center for Urban Science and Progress (CUSP). My research interests are in probabilistic machine learning and Bayesian statistics with an emphasis on the study and integration of various forms of structure and inductive biases (structured priors, spatiotemporal dependencies, d

代表成果

• Terje Mildner, MEng in CS/Discrete Math, 3rd year Discrete Math thesis project, Outstanding 3rd year project award in CS, Partitioned/Federated Generalised Variational Inference, Dept. of Computer Science, University of Warwick, 2024. [co-supervised with Dr. Oliver Hamelijnck]
• James Walsh, BSc in Data Science, Physics-informed machine learning of Li-ion 18650 battery degradation, Dept. of Statistics & Dept. of Computer Science, University of Warwick, 2019. [co-supervised with Dr. Daniel Tait]
• Patrick O'Hara, BSc in Computer Science, Running NP-Hard from Air Pollution: Graph optimisation algorithms, Dept. of Computer Science, University of Warwick, 2018. [co-supervised with Dr. Ramanujan Sridharan]
• Yannis Zachos, BSc in Data Science, Bayesian Online Changepoint Detection: Spatio-temporal point processes, Dept. of Statistics & Dept. of Computer Science, University of Warwick, 2018. [co-supervised with Jeremias Knoblauch]
• Giorgos Felekis, MSc in Machine Learning,Thesis, Paper: Generalised Variational Inference posteriors in Probabilistic Deep Learning, UCL, 2020. [co-supervised with Dr. Brooks Paige]
• Johannes Muller, MSc in Interdisciplinary Mathematics, Parameter estimation and consistency for discrete determinantal point processes, Dept. of Mathematics, University of Warwick, 2018. [co-supervised with Prof. Nikolaos Zygouras]
• Edoardo Barp, MSc in Mathematics for Real World Systems, Bayesian Inverse Reinforcement Learning for path-based reward inference, Dept. of Mathematics, University of Warwick, 2018. [co-supervised with Virginia Aglietti]
• Best Paper Award, 2024 Wilkes Award, The Computer Journal, 2024
• Best Paper Award, AISTATS, 2022
• Turing AI Acceleration Fellowship, UKRI, 2021-2026