Isabelle Guyon

Timeline

1. 1988

   A doctorate in Paris

   She graduates from the École Supérieure de Physique et Chimie Industrielles in Paris, then earns a PhD in Physical Sciences at Université Pierre et Marie Curie in 1988.

2. 1991

   Developing a support vector machine

   During postdoctoral research, she meets Vladimir Vapnik in 1991; together they develop the support vector machine for data classification. She works at Bell Labs for seven years and later moves to Berkeley.

3. 1996–2011

   Machine learning challenges

   She creates the Coplinet consultancy in 1996, then founds ChaLearn in 2011 to teach machine learning through challenges that attract thousands of entrants.

4. 2003

   Selecting useful features

   With André Elisseeff, she publishes the JMLR article “An Introduction to Variable and Feature Selection.” It presents variable selection as a way to improve prediction, make predictors faster and more cost-effective, and clarify the process that generated the data.

5. 2003

   Testing feature selection

   With Steve Gunn, Asa Ben-Hur, and Gideon Dror, she organizes the NIPS 2003 feature-selection competition. It gives participants five data sets and attracts 78 research groups.

6. 2015–2025

   Teaching and chairing NeurIPS

   She taught machine learning and advised graduate students at Université Paris-Saclay. From 2019 to 2021, she coordinated its CS Artificial Intelligence master's program; she served as NeurIPS co-program chair in 2016 and co-general chair in 2017.

7. 2019

   Recognition for machine learning

   She shared the BBVA Foundation Frontiers of Knowledge Award in Information and Communications Technology with Bernhard Schölkopf and Vladimir Vapnik for their fundamental contributions to machine learning.

8. As of October 2026

   Research at Google DeepMind

   She is a Director and Research Scientist at Google DeepMind, where she studies AI self-improvement and AI use in peer review. In 2026, she is president of ChaLearn.