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Intelligent Earth Seminar: Marc Deisenroth (UCL)

Opportunities for Machine Learning to Accelerate Progress in Environmental Modelling

20 November 2024

 

Professor Marc Deisenroth is the Google DeepMind Chair of Machine Learning and Artificial Intelligence at University College London. He also holds a visiting faculty position at the University of Johannesburg. Marc co-leads the Sustainability and Machine Learning Group at UCL. His research interests center around data-efficient machine learning, probabilistic modeling and autonomous decision making with applications in climate/weather science, nuclear fusion, and robotics. Marc was Program Chair of EWRL 2012, Workshops Chair of RSS 2013, EXPO Chair at ICML 2020, Tutorials Chair at NeurIPS 2021, and Program Chair at ICLR 2022. He is an elected member of the ICML Board. He received Paper Awards at ICRA 2014, ICCAS 2016, ICML 2020, AISTATS 2021, and FAccT 2023. Marc is co-author of the book Mathematics for Machine Learning, published by Cambridge University Press.

Abstract

Modelling complex environmental systems, such as weather or oceans, is extremely challenging. Recent advances in machine learning and AI to automatically learn complex relationships from data have opened up opportunities for data-driven methodologies to make a meaningful contribution to environmental science and even play the role of a transformative technology within environmental modelling. In this talk, I will focus on some of our recent work on using machine learning for data assimilation and medium-range weather forecasting.