Michael Bronstein

Michael Bronstein is a Professor & Chair in Machine Learning and Pattern Recognition at the Department of Computing, Imperial College London (since 2018), with a concurrent professorship at the Institute for Computational Science, University of Lugano, Switzerland (since 2010, currently on leave). His academic career includes visiting positions at Stanford University (Visiting Lecturer, 2008-2009), Tel Aviv University (Visiting Associate Professor, 2015-2017), Harvard University (Visiting Scholar, 2017-2018), and MIT (Research Affiliate, 2017-2018).

Dr. Bronstein's research focuses on theoretical and computational geometric methods for data analysis, with applications spanning machine learning, computer vision, graphics, geometry processing, biology, and social networks. His work in geometric deep learning has established foundational frameworks for processing non-Euclidean data such as graphs and manifolds, bridging the gap between traditional Euclidean deep learning and complex structured data.

His publication record demonstrates a clear trajectory from fundamental geometric methods to their application in diverse domains. Early work focused on 3D shape analysis and non-rigid shape recognition, while more recent publications showcase the application of geometric deep learning to protein structure analysis, point cloud processing, and graph-based machine learning. The consistent thread throughout his research is the development of mathematical frameworks that respect the intrinsic geometry of data.

• Royal Academy of Engineering Silver Medal (2020)
• Fellow of IEEE, IAPR, and ELLIS
• Five ERC grants (Starting 2012, Consolidator 2016, and Proof of Concept 2016, 2018, 2019)
• Royal Society Wolfson Research Merit Award
• Young Scientist, World Economic Forum (2014)

Bronstein has successfully translated academic research into practical applications through multiple entrepreneurial ventures. As ML Lead for Project CETI and Head of Graph Learning Research at Twitter (since 2019), he bridges academic research with industrial applications. His previous startups include Fabula AI (acquired by Twitter in 2019) and Invision (acquired by Intel in 2012), where he contributed to the development of Intel RealSense 3D camera technology. His research has been supported by significant funding including ERC grants and industry awards from Google, Amazon, and Facebook.