About the Talk:
One of the pillars of scientific progress, the peer review system, is facing unprecedented challenges. The pressure to publish, coupled with the lack of adequate incentives for reviewers, the sheer volume of submissions, and the difficulties in finding relevant expertise, are pushing the system towards a breaking point. The rise of sophisticated language models (LLMs) has added another layer of complexity, exacerbating the problem by facilitating the generation of potentially low-quality or even fabricated content. However, these very same technological advancements promise to improve the peer review process. In this presentation, we will review recent progress in this area.

Bio:
Isabelle Guyon is Director, Research Scientist at Google, in detachment from her position as professor of Artificial Intelligence at Université Paris-Saclay (Orsay). She specializes in data-centric AI, statistical data analysis, pattern recognition, and machine learning. Her areas of expertise include computer vision, bioinformatics, and power systems. Her recent interests include meta-learning, causal discovery, AI fairness and safety, and Generative AI. Prior to joining Paris-Saclay she worked as an independent consultant and was a researcher at AT&T Bell Laboratories, where she pioneered applications of neural networks to pen computer interfaces (with collaborators including Yann LeCun and Yoshua Bengio) and co-invented with Bernhard Boser and Vladimir Vapnik Support Vector Machines (SVM), which became a textbook machine learning method. She is also the primary inventor of SVM-RFE, a variable selection technique based on SVM. The SVM-RFE paper has thousands of citations and is often used as a reference method against which new feature selection methods are benchmarked. She also authored a seminal paper on feature selection that received thousands of citations.  She organized many challenges in Machine Learning since 2003 supported by the EU network Pascal2, NSF, DARPA, and the European Commission, with prizes sponsored by Microsoft, Google, Facebook, Amazon, Disney Research, and Texas Instrument. Isabelle Guyon holds a Ph.D. degree in Physical Sciences of the University Pierre and Marie Curie, Paris, France. She is president of Chalearn, a non-profit dedicated to organizing challenges, action editor of the Journal of Machine Learning Research, editor of the Springer series of Challenges in Machine Learning, and served as program co-chair of NIPS 2016, general co-chair of NIPS 2017, and NeurIPS board member 2018-2024. She serves on the board of Kaggle. She is a 2020 recipient of the BBVA Frontiers in Research Award together with Prof. Schoelkopf and Prof. Vapnik and a member of the French Academy of technologies since 2024.