Lars Schaaf

Lars Schaaf is a Junior Research Fellow at Wolfson College, University of Cambridge, affiliated with the Department of Engineering within the School of Technology. His work bridges machine learning and computational physics to revolutionize atomic-scale simulation capabilities.

His research focuses on accelerating physical simulations through machine learning, enabling unprecedented atomic-resolution analysis of real-world processes like drug-protein binding and battery ion diffusion. Key interests include:

• Machine Learning for Scientific Computing
• Computational Materials Science
• Quantum Mechanical Simulations
• Energy Storage Materials
• Electrostatic Modeling for Batteries/Supercapacitors
• Catalysis for Renewable Energy

Current work targets precise electrostatic effect modeling in energy-transition materials, where charge distribution accuracy is critical for next-generation batteries and electro-catalysts. His PhD developed ML-accelerated simulation frameworks for catalytic reaction analysis aimed at reducing global energy consumption, including novel architectures for non-local interaction capture.

Academic background spans Theoretical Physics (Birmingham, Astrophysics focus) to Condensed Matter Physics (Cambridge Master's), with early scientific computing experience at the Max Planck Institute for Nuclear Physics developing cosmic x-ray observation systems.