معرفی
Dr. Stefan Klus is a Lecturer at the School of Mathematics and Physics, University of Surrey. His research focuses on data-driven model reduction, transfer operator approximation, and kernel-based machine learning applied to dynamical systems. He specializes in interdisciplinary applications across quantum physics, fluid dynamics, and computational biology.
Education: PhD in Industrial Mathematics (2011, Paderborn University) and Habilitation (2020, Freie Universität Berlin).
Research Interests:
- Data-driven modeling and reduced-order methods
- Koopman operator theory and transfer operators
- Machine learning for dynamical systems (e.g., Deeptime library)
- Tensor decompositions and quantum systems analysis
- Graph-based analysis (e.g., microbiome dynamics)
Publications: Klus has contributed to over 50 peer-reviewed articles, with recent work emphasizing:
- Kernel methods for quantum chemistry and physics
- Tensor-based approaches for high-dimensional systems
- Applications in climate science (e.g., Pacific SST modeling)
- Agent-based modeling and social systems
Technical Contributions:
- Co-developer of the Deeptime Python library for dynamical modeling
- Pioneer in Koopman operator-based model reduction
- Advanced graph kernel methods for microbiome analysis
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