Speakers & Topics
Speakers at MLSS

Academics and practitioners

Speakers & Topics

Following experts will be speaking at the school

MRI

Michel Besserve

Topological Data Analysis

Ulrich Bauer

Graph Neural Networks

Michael Bronstein

Michael Bronstein (PhD 2007, Technion, Israel) is a professor at Imperial College London, where he holds the Chair in Machine Learning and Pattern Recognition and Royal Society Wolfson Merit Award. He holds/has held visiting appointments at Stanford, Harvard, MIT, and TUM. Michael's main research interest is in theoretical and computational methods for geometric data analysis. He is a Fellow of IEEE and IAPR, ACM Distinguished Speaker, and World Economic Forum Young Scientist. He is the recipient of multiple prestigious awards, including four ERC grants, two Google Faculty awards, and the 2018 Facebook Computational Social Science award. Besides academic work, Michael was a co-founder and technology executive at Novafora (2005-2009) developing large-scale video analysis methods, and one of the chief technologists at Invision (2009-2012) developing low-cost 3D sensors. Following the multi-million acquisition of Invision by Intel in 2012, Michael has been one of the key developers of the Intel RealSense technology in the role of Principal Engineer. His most recent venture is Fabula AI, a startup dedicated to algorithmic detection of fake news using geometric deep learning.

Online Learning

Nicolò Cesa-Bianchi

Nicolò Cesa-Bianchi is professor of Computer Science at the University of Milan, Italy. His main research areas include the design and analysis of machine learning algorithms, particularly in the online learning model, the study of algorithms for multiarmed bandit problems with applications to personalized recommendations and online auctions, and graph analytics with applications to social networks and bioinformatics. He is co-author of the monographs "Prediction, Learning, and Games" and "Regret Analysis of Stochastic and Nonstochastic Multi-armed Bandit Problems".

Kernels

Arthur Gretton

Causality

Joris Mooij