I am a Ph.D. student in the Department of Electrical and Computer Engineering at The University of Texas at Austin, advised by Prof. Aryan Mokhtari. I work on optimization for machine learning, with a focus on algorithms that are both theoretically principled and practically effective. Recently, my work has explored nonconvex optimization, online-learning-based methods, and adaptive optimizers.

I am also open to internship opportunities in optimization, machine learning, and quantitative research.

Before joining UT Austin, I earned my engineering degree from the Universidad Nacional de La Plata, where I received the 2022 Ing. Isidoro Marín Medal from the National Academy of Engineering of Argentina. I also pursued graduate studies in Mathematical Engineering at the Universidad de Buenos Aires.

Publications

For a complete list see my Google Scholar profile.

Improving Online-to-Nonconvex Conversion for Smooth Optimization via Double Optimism

F. Patitucci, R. Jiang, A. Mokhtari

International Conference on Learning Representations (ICLR), 2026 Paper

Improved Complexity for Smooth Nonconvex Optimization: A Two-Level Online Learning Approach with Quasi-Newton Methods

R. Jiang, A. Mokhtari, F. Patitucci

Proceedings of the 57th Annual ACM Symposium on Theory of Computing (STOC), 2025 Paper