Ron Dror

Timeline

1. 2002–2014

   First hire at D. E. Shaw Research

   A Rice graduate in mathematics and in electrical and computer engineering, with an MPhil in biological sciences from Cambridge as a Churchill Scholar and an MIT PhD in electrical engineering and computer science, he joins D. E. Shaw Research in 2002 as its first hire. He becomes second-in-command of the hundred-person company and develops technology that accelerates molecular dynamics simulations by orders of magnitude.

2. 2009–2014

   Two Gordon Bell Prizes

   He receives the ACM Gordon Bell Prize for Special Achievement in 2009 and the ACM Gordon Bell Prize for Performance in 2014. A D. E. Shaw Research project that includes his protein-simulation work is highlighted by Science among the top 10 scientific breakthroughs of 2010.

3. March 2014

   Moving to Stanford

   He joins Stanford University in March 2014, where his research addresses computational biology problems related to the spatial organization and dynamics of biomolecules and cells.

4. August 2021

   ARES for RNA structure

   In August 2021, he and Rhiju Das co-lead the Science paper "Geometric deep learning of RNA structure", with Stanford PhD students Stephan Eismann and Raphael Townshend assisting. The paper introduces ARES, the Atomic Rotationally Equivariant Scorer, a neural network trained on only 18 known RNA structures that consistently produces the best results in community-wide blind RNA structure prediction challenges.

5. 2021

   ATOM3D and a NeurIPS award

   He coauthors ATOM3D: Tasks on Molecules in Three Dimensions with Raphael Townshend, Russ Altman and others, a collection of benchmark datasets spanning several key classes of biomolecules with an open-source atom3d Python package. The paper receives a Datasets and Benchmarks Award at NeurIPS in 2021.

6. 2023

   The Cheriton Family Professorship

   Stanford University gives him the Cheriton Family Professorship in 2023, an appointment in computer science.

7. As of October 2026

   Professor in the Stanford AI Lab

   He is the Cheriton Family Professor of Computer Science in the Stanford Artificial Intelligence Lab and a professor, by courtesy, of structural biology and of molecular and cellular physiology. In March 2025, he gives a Duke seminar on discovering safe, effective drugs through machine learning and simulation of 3D structure. His group uses molecular simulation and machine learning to elucidate biomolecular structure, dynamics and function, and to guide the development of more effective medicines.