Leonardo Galli

Postdoc Researcher
LMU Munich

I am a researcher working on optimization for machine learning. I am currently focusing on deep learning and its mathematical foundations. My goal is to design optimization methods whose successful outcome can be provably ensured when applied to deep learning. I am interested in large-scale optimization, (nonmonotone) line search methods for deep learning, the Edge of Stability phenomenon, Sharpness-Aware-Minimization and all that.

Short bio: I obtained my B.S., M.S. and Ph.D. degrees from University of Florence respectively in 2013, 2016 and 2020. My Ph.D. advisors and mentors there were prof. Marco Sciandrone and prof. Fabio Schoen. To avoid stereotypical comments on italians, I tried to escape my hometown a few times during my studies (University of Würzburg in 2015, UCLA in 2019 and National Taiwan University in 2020, all documented in my photograpic logbook and by my papers). From 2015 to 2017 I collaborated with prof. Christian Kanzow on generalized Nash equilibrium problems and from 2018 to 2020 with prof. Chih-Jen Lin on truncated Newton methods for linear SVM. In 2021 I moved to RWTH Aachen, where I won the 2 years KI-starter personal grant from North-Rhine Westphalia. Since then I collaborate with prof. Holger Rauhut and prof. Mark Schmidt on line search methods for deep learning. I am now Senior Postdoc at LMU Munich since 2023.

Invited Talks

2024-11: University of Genova MaLGa Seminars

2024-07: ISMP Conference Numerical Optimization for Machine Learning

2024-07: EURO Conference Advances in Large Scale Optimization

2024-06: Dataninja sAIoNARA Conference Highlights KI-Starter

2024-06: TUM Theoretical Foundations of Artificial Intelligence

2024-04: CISPA Trustworthy Information Processing Group