Dr. Francis Bach is a preeminent researcher at INRIA where he has led the SIERRA project-team since 2011 as part of the Computer Science Department at Ecole Normale Supérieure in Paris. He completed his formal education at France's most prestigious institutions, graduating from Ecole Polytechnique in 1997 before earning his Ph.D. in Computer Science from the University of California, Berkeley in 2005 under the supervision of Professor Michael Jordan. His early career included two years in the Mathematical Morphology group at Ecole des Mines de Paris, followed by a significant tenure at the Willow project-team at INRIA/Ecole Normale Supérieure from 2007 to 2010. This distinguished career path established him as a leading authority in theoretical machine learning with exceptional mathematical foundations.
Dr. Bach has made transformative contributions to statistical machine learning, particularly in the areas of sparse methods, kernel-based learning, graphical models, and large-scale convex optimization. His research has profoundly influenced both theoretical frameworks and practical implementations of machine learning algorithms, with his scholarly work accumulating over 73,000 citations as documented in Google Scholar. The development of efficient optimization techniques for high-dimensional problems has been instrumental in advancing the field, enabling sophisticated analysis of complex datasets across numerous scientific domains. His 2014 ICML test-of-time award and 2018 Lagrange prize in continuous optimization recognize the enduring significance and mathematical elegance of his methodological breakthroughs.
As a visionary leader in the machine learning community, Dr. Bach served as program co-chair of the International Conference on Machine Learning in 2015 and general chair in 2018, while currently serving as co-editor-in-chief of the Journal of Machine Learning Research. His election to the French Academy of Sciences in 2020 represents one of the highest scientific honors in France, underscoring his impact on the broader scientific landscape. Dr. Bach currently leads the ERC project SEQUOIA, building upon his previous ERC-funded SIERRA project, to advance fundamental understanding of machine learning theory and practice. His ongoing research continues to shape the trajectory of methodological development in machine learning, focusing on theoretical guarantees for learning algorithms while maintaining strong connections to practical applications in computer vision and signal processing.
