About
Rouven Koch is a Visiting Professor at Aalto University's Department of Applied Physics, School of Science. His research focuses on merging machine learning with quantum materials and condensed matter physics, particularly in topological superconductors, quantum dots, and Kitaev chains.
His work leverages adversarial and generative machine learning techniques to infer Hamiltonians, control quantum systems, and design novel quantum matter. Key areas include scanning tunneling microscopy, spin resonance, and superconductor material analysis.
Recent trends highlight applications in triplon excitations (2025), autonomous control of quantum chains (2024), and Hamiltonian learning for impurity tomography in moiré superconductors (2024). Collaborations include J. Lado, M. Khosravian, and E. Greplova.
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