The Manchester Centre for AI Fundamentals and Manchester's ELLIS Unit are co-hosting a series of seminars featuring expert researchers working in the fundamentals of AI.

On 18 June, we are joined by Prof Theo Damoulas from the University of Warwick.

Title: Distributionally Robust Optimisation with Bayesian Ambiguity Sets

Bio: I am a Professor in Machine Learning and Data Science with a joint appointment in Computer Science and Statistics. I am a Turing AI Fellow (2021-2026) having received the UK Research and Innovation (UKRI) Turing AI Acceleration Fellowship 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, dynamics, compositions, physical laws, flows, causality, etc) while advancing robust and scalable approximate inference methodologies. My research has broad applications in Digital Twins, Bayesian nonparametrics and spatiotemporal problems in urban science and computational sustainability. I am the founder and PI of the cross-departmental Warwick Machine Learning Group and I lead two large projects at The Turing that are impact stories.

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Centre for AI Fundamentals (AI-FUN) is inviting you to a scheduled Zoom meeting.
Join Zoom Meeting
https://zoom.us/j/97677103903

Meeting ID: 976 7710 3903