Dan Berenberg, PhD

About me

I worked on a variety of sequence generative modeling and protein property prediction tasks that culminated in my doctoral thesis titled “Modern Machine Learning Methods for Protein Design”. I was advised by Richard Bonneau and Kyunghyun Cho at NYU in the Computer Science department of the Courant Institute.

Most of my PhD work stems from my time at Prescient Design, where I was a founding member (employee #1) from the early startup days through the acquisition by and integration into Genentech/Roche. Prior to Prescient/NYU I worked in the protein structure/function subgroup of the Systems Biology lab at the Flatiron Institute.

Before that, I completed an accelerated Master’s at UVM advised by James Bagrow with work on understanding causal attribution networks.

Education

• PhD, New York University, 2025
• MSc, University of Vermont, 2019
• BS Mathematics, University of Vermont, 2017