Miles Cranmer

Miles Cranmer is an Assistant Professor in Data Intensive Science at the University of Cambridge, affiliated with the Department of Applied Mathematics and Theoretical Physics (DAMTP) and the Institute of Astronomy (IoA). His research focuses on AI for scientific discovery, particularly in symbolic regression, machine learning for physics, and large-scale data analysis in astrophysics.

He leads the AstroAutomata research group, which develops open-source tools like PySR and SymbolicRegression.jl for symbolic regression. Cranmer's work bridges machine learning and domain sciences, with applications ranging from galaxy evolution to planetary dynamics.

Key research themes include:

• Interpretable AI for scientific modeling
• Surrogate models for PDEs and physics simulations
• Benchmarking frameworks for symbolic regression

His recent publications explore novel methods in symbolic regression, physics-informed machine learning, and large-scale astronomical data analysis. Cranmer actively contributes to open-source software ecosystems for scientific computing.