Farshud Sorourifar

Farshud Sorourifar develops machine learning and optimization methods for discovering new materials and molecules, including battery electrode materials and molecular designs, and applies these techniques to speed up quantum computing algorithms. Much of the work combines Bayesian optimization, symbolic regression, and other data-driven tools with chemistry and physics problems to make model discovery more efficient and interpretable.

Publication output has grown substantially over the last decade, rising from occasional single papers before 2023 to 9-11 publications per year in 2024-2025.

Generated by claude-sonnet-5 from public bibliographic data · Jul 20, 2026