Alessandro Simon

Coding, Physics, ML

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University of Tübingen

72076 Tübingen, Germany

Hi, I’m a PhD student in physics and machine learning at the university of Tübingen, working with M. Oettel and G. Martius. My work focuses on the intersection of statistical mechanics, specifically classical fluids and machine learning methods.

Broadly speaking, we look at classical many-body systems by doing computer simulations and analyzing the results. In parallel we try to develop theories that describe the behavior that we observed. Our tool of choice is classical density functional theory. In order to find accurate functionals (i.e. make predictions) we use different machine learning methods.

selected publications

  1. JCTC
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    Machine learning of a density functional for anisotropic patchy particles
    Alessandro Simon, Jens Weimar, Georg Martius, and Martin Oettel
    Journal of Chemical Theory and Computation, 2024
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  2. arXiv
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    Machine Learning approaches to classical density functional theory
    Alessandro Simon, and Martin Oettel
    arXiv preprint arXiv:2406.07345, 2024
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