Kalman Szenes is a computational scientist and software engineer focused on developing high-performance algorithms for electronic structure and computational physics. As a PhD student in Quantum Chemistry at ETH Zurich and a scientific software engineer with experience at CSCS, Algorithmiq, and Xanadu, he specializes in GPU-accelerated tensor network methods and optimized tensor algorithms for chemical systems. He combines rigorous academic training in chemistry and computational science with practical expertise implementing GPU-enabled numerical schemes like DG methods via domain-specific languages. Kalman’s work sits at the intersection of theory and performance engineering, translating advanced tensor-network theory into scalable code for quantum computing and simulation. Based in the Zürich area, he brings five years of hands-on experience and a track record of turning complex mathematical ideas into production-grade HPC implementations.
5 years of coding experience
1 year of employment as a software developer
Exchange Student Chemistry, Exchange Student Chemistry at Imperial College London
Bachelor's degree Chemistry and Chemical Engineering, Bachelor's degree Chemistry and Chemical Engineering at EPFL
Master's degree Computational Science and Engineering, Master's degree Computational Science and Engineering at ETH Zürich
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Kalman Szenes - PhD Student In Quantum Chemistry at ETH Zürich