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Data-driven Simulation of Complex Systems

Dr. Matthias Rupp (Universität Konstanz)

Art des Termins
    Wann 10.02.2022
    von 12:15 bis 13:15
    Wo Zoom
    Termin übernehmen vCal

    Data-driven algorithms ("machine learning") are increasingly used in science and engineering for analysis, prediction, and control, enabling new insights and applications. For this, tight integration of domain knowledge is often crucial. At the example of atomistic simulations in physics, chemistry, materials science, and pharmaceutical sciences, I will demonstrate how domain-enhanced machine-learning models enable large-scale exploration of molecular and materials spaces for the discovery, study, and design of molecules and materials; simulating large atomistic systems over long time scales; and accurate and precise property predictions. I will present selected current projects, including message-passing neural networks for Green-Kubo thermal conductivities and "ultra-fast" machine-learning force fields, and provide an outlook on long-term research directions.