DANIEL FREEDMAN

Daniel Freedman's current research focuses on the application of artificial intelligence to the natural sciences.  He pursues this research program through two different avenues:

1. At Tel Aviv University, he is a Visiting Professor of Applied Mathematics.  His research group is mainly focused on solving problems in both quantum physics and partial differential equations, using new numerical techniques based on Generative AI.

2. At Genesis Molecular AI, he is a Distinguished Research Scientist.  He develops algorithms, which combine AI and physics, for the design of entirely new molecules.
    

Previously, Daniel was Head of the Fundamental Research: Science group at Verily (= Google Life Sciences); and Research Scientist at Google Research, Microsoft Research, IBM Research, and HP Labs.  Prior to that, he was a professor for nearly a decade, mainly at Rensselaer Polytechnic Institute (RPI), but with stops also at Bar Ilan University and as a Fulbright Fellow at the Weizmann Institute of Science.
 

Older research included work on:

• Novel Imaging Modalities: nanoscale imaging; hyperspectral microscopy; full waveform inversion ultrasound; theory of inverse problems.

• Computational Algebraic Topology: optimal bases for homology groups.

• Mathematical techniques in computer vision and signal processing: geometric PDEs and combinatorial optimization.
   

Over the years, Daniel's work has received several honors, including the National Science Foundation CAREER Award; the Fulbright Fellowship; and several best paper awards.  Additionally, he has been an investigator on a number of grants from NSF, NIH, and the US Army.  Daniel received his AB in Physics from Princeton University (Magna Cum Laude, Phi Beta Kappa, Sigma Xi), and his PhD from the Division of Applied Sciences at Harvard University.