
About
Michał Sanocki is a researcher in the Department of Mechanical Engineering at Technische Universität München (TUM), affiliated with the Multiscale Modeling of Fluid Materials group. His work bridges computational chemistry, materials science, and machine learning, with a focus on Metal Organic Frameworks (MOF) and non-local molecular interactions.
- Education: MSc in Computational Science (University of Amsterdam, 2024), BSc in Chemistry (University of Warsaw, 2022), and BSc in Quantitative Methods (Warsaw School of Economics, 2021).
Sanocki's research leverages graph neural networks and physics-informed machine learning to model complex fluid materials. His recent publications highlight applications in catalyst risk assessment and equivariant representations for molecular simulations.
He is associated with the Atomistic Modeling Center (AMC) and Munich Data Science Institute (MDSI), contributing to projects that integrate machine learning with uncertainty quantification for physics-based models. Contact: m.sanocki@tum.de.
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