My full CV is available in pdf form here.
I received three bachelor's degrees in math, applied math, and statistics from Chico State University in 2015. I then did a master's degree in applied math with a concentration in nonlinear dynamical systems at San Diego State University where I studied under Jérôme Gilles. My master's thesis was titled "The Empirical Gabor Transform and Empirical Gabor Frames" and I defended it in 2017. After this I went to Université de Caen Normandie in the GREYC laboratory IMAGE team from 2017-2021 where I did a PhD in math under Jalal Fadili and Gabriel Peyré. My PhD thesis was titled "First-order noneuclidean splitting methods for large-scale optimization: deterministic and stochastic algorithms". I was a postdoc at the Toulouse School of Economics under Jérôme Bolte and Edouard Pauwels from February 2021 until August 2022. Since September 2022 I have joined Université de Paris-Saclay as a maître de conférences (~associate professor or assistant professor with a permanent contract).
Recent grants and awards are listed on the grants page.
Antonio (Tony) Silveti-Falls is an associate professor (maître de conférences) at CentraleSupélec in the south of Paris, where he is a member of the Centre pour la Vision Numérique laboratory and the INRIA team OPIS. After receiving his PhD in mathematics from Université de Caen Normandie in 2021, where he was supervised by Jalal Fadili and Gabriel Peyré, he completed a postdoc at Toulouse School of Economics with Jérôme Bolte and Edouard Pauwels. His research continues to focus on {nonsmooth, stochastic, noneuclidean} optimization, especially conditional gradient methods (Frank-Wolfe) and conservative calculus (path differentiable functions) applied to deep learning. His work on the generalized conditional gradient method won the best paper award at SPARS 2019.