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Director, Research Scientist, Google DeepMind (since Oct 2022).

Chaired Professor of Artificial Intelligence (PR EX1) and INRIA researcher, Machine Learning and Optimization (TAU team), Laboratoire Interdisciplinaire des Sciences du Numérique (LISN) University Paris-Saclay, France

Graduate of ESPCI. PhD in Paris in Gerard Dreyfus' Lab. Worked at Bell Labs for 7 years, then moved to Berkeley, California. Three children with Bernhard Boser. Independent consultant with ClopiNet. 

Since 2015, Full Professor at Université Paris-Saclay:  Teaching Machine Learning and advising graduate students. 2019-2021, coordinator of CS Artificial Intelligence master program at UPSaclay.

Co-program chair of NeurIPS 2016 and co-general chair of NeurIPS 2017. [what the press says]; then NeurIPS board member. AMIA and an ELLIS fellow. Action editor at JMLR, and DMLR, CiML springer series editor. BBVA award recipient (2020).

Recent awards and honnors: Ten-Year Technical Impact Award ICMI, 2023; Best paper award 19th IEEE conference on e-Science, 2023, nominated to the French Academy of Techinologies.

President of ChaLearn

Bear Valley, California

501(c)(3) non-profit organizing challenges

Since 2003 machine learning challenge organizer. Using challenges as a means of directing research in domains including: causality, computer vision, automatic machine learning, and high energy physics.

ChaLearn collaborates with the open-source Codalab competitions project , of which I am community lead.

We received a large EU grant to organize the 2 million Euro See.4C challenge with data from RTE. The winners have been announced. We also co-organized two AI for Industry challenges with Dassault Aviation and RTE France, funded by Région Ile-de-France. See the results of the latest L2RPN challenge.

Our current projects include Looking at People,  TrackML, Meta-Learning challenges, and Learning to run a Power Network, and systematic bias in computer vision, medical data, and bias in High Energy Physics (HEP) simulations. We also study how to use AI to review scientific papers and conducted a study on whether large language models could contribute to helping authors improve their papers.