Simone Bombari

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Hi! I am Simone Bombari, thanks for visiting my website! :muscle:

I am a PhD student at ISTA, happy and lucky to be advised by Professor Marco Mondelli. Right now, I enjoy thinking about research questions connected with deep learning, high dimensional probability, and trustworthy machine learning. For example, I like to think if over-parameterized models trained on high-dimensional data hide some not-necessarily-trivial behavior, with maybe some implications connected to privacy or robustness.

Before joining ISTA I studied Physics at Scuola Normale Superiore and University of Pisa. During my studies, I focused on statistical physics and quantum information. Then, I slowly migrated towards statistics and machine learning. :computer:

During my PhD, I had the opportunity to intern as an applied scientist at AWS, and as NLP quant researcher at G Research. Since the fall of 2024, I am supported by a Google PhD fellowship.

During spring and summer 2025, I was a visiting scholar at the University of Southern California, in the groups of Yizhe Zhu and Mahdi Soltanolkotabi.

Of course, I have many interests beyond my research. I have a deep passion for sports, fitness, games and many other things! :soccer:

selected publications and preprints

  1. optimization.png
    Memorization and Optimization in Deep Neural Networks with Minimum Over-parameterization
    Simone Bombari ,  Mohammad Hossein Amani ,  and  Marco Mondelli
    NeurIPS - contributed talk at DeepMath, 2022
  2. no_muscle.jpg
    Beyond the Universal Law of Robustness: Sharper Laws for Random Features and Neural Tangent Kernels
    Simone Bombari ,  Shayan Kiyani ,  and  Marco Mondelli
    ICML - selected for oral presentation, 2023
  3. privacy.png
    Privacy for Free in the Overparameterized Regime
    Simone Bombari ,  and  Marco Mondelli
    PNAS - contributed talk at DeepMath, 2025
  4. DP-SGD-ODE_new.png
    Better Rates for Private Linear Regression in the Proportional Regime via Aggressive Clipping
    Simone Bombari ,  Inbar Seroussi ,  and  Marco Mondelli
    arXiv, 2025
  5. reconstruction.png
    A Law of Data Reconstruction for Random Features (and Beyond)
    Leonardo Iurada ,  Simone Bombari ,  Tatiana Tommasi , and 1 more author
    arXiv, 2025