Gábor Csányi
Also known as Gabor Csanyi
Gábor Csányi develops machine-learning methods for atomistic modeling. His research connects quantum calculations to models that can simulate larger material systems. Csányi coauthored the original Gaussian Approximation Potentials preprint with Albert Bartók, Mike Payne and Risi Kondor. It learns interatomic models from quantum-mechanical energies and forces. He is a professor of molecular modeling at Cambridge. His research includes force fields learned from electronic-structure data and methods for sampling molecular configurations. In 2024, his research interests included atomistic models that work across many elements, compounds and structures.
- Now at
- University of Cambridge
- Works
- 364
- Citations
- 29,904
- h-index
- 75
Publication numbers from OpenAlex, as of 14 October 2026.
Timeline
-
2009
Gaussian Approximation Potentials
Csányi coauthored the original Gaussian Approximation Potentials preprint with Albert Bartók, Mike Payne and Risi Kondor. It learns interatomic models from quantum-mechanical energies and forces.
-
2024
Foundation models for chemistry
In 2024, his research interests included atomistic models that work across many elements, compounds and structures.
-
As of October 2026
Molecular modeling at Cambridge
He is a professor of molecular modeling at Cambridge. His research includes force fields learned from electronic-structure data and methods for sampling molecular configurations.
Sources and credits
Photo: ellis.eu; Gábor Csányi profile photograph; creator not stated. License: Not stated by source. Source: ellis.eu. Cropped to a square and resized. Ask us to remove or replace this photo.