Anatole von Lilienfeld

Professor Anatole von Lilienfeld is affiliated with the University of Toronto's Department of Chemistry and Department of Materials Science & Engineering, with cross-appointments to the Department of Physics and the Vector Institute. His research focuses on quantum machine learning for chemical compound space exploration, combining physics-based models with high-performance computing.

• Chemical Physics
• Quantum Machine Learning
• Computational Materials Design
• Density Functional Theory
• Molecular Dynamics
• Excited States
• Nuclear Quantum Effects

His recent work demonstrates how machine learning accelerates solving the Schrödinger equation for novel materials, achieving speedups of multiple orders of magnitude compared to traditional quantum chemistry methods. Key contributions include Coulomb matrix representations and alchemical perturbation techniques.

Scientific achievements include the Ed Clark Chair for Advanced Materials and an ERC Consolidator Grant. He leads the Chemspacelab, an interdisciplinary team developing open-source tools like LERULI.com for real-time molecular property predictions.