After earning a Masters of Engineering from Ecole Centrale Paris, Simon Foucart received his PhD in Mathematics from the University of Cambridge in 2006. He took two postdoctoral positions, at Vanderbilt University and at Paris 6 University, before joining Drexel University in 2010 and moving to the University of Georgia in 2013. Since 2015, he has been with Texas A&M University, where he became Professor and Presidential Impact Fellow in 2019. He also held short visiting appointments at University of Bonn, University of South Florida, Hong Kong University of Science and Technology, CNRS Toulouse, and University of Wisconsin-Madison.
Dr. Foucart's most influential work to-date revolves around the field of Compressive Sensing. His contribution was recognized by the 2010 Best Paper Award from the Journal of Complexity. His current interests include the mathematical aspects of Metagenomics, Optimization, Deep Learning, and Data Science at large. He serves on the editorial board of Journal of Approximation Theory, of Journal of Numerical Mathematics, and of Sampling Theory, Signal Processing, and Data Analysis.
Aside from 50+ peer-reviewed research articles, Dr. Foucart has written two graduate-level textbooks: 'A Mathematical Introduction to Compressive Sensing' (with Holger Rauhut, Birkhauser) and 'Mathematical Pictures at a Data Science Exhibition' (to appear, Cambridge University Press).