My name is Evan Seitz and I recently obtained a doctorate with distinction at Columbia University working on Computational Biophysics in the Frank Lab. I am interested in studying complex biophysical systems through a mathematically-rigorous and creative lens. My thesis work is based on a geometric machine-learning approach to study hundreds of thousands of unorganized, extremely noisy single-particle cryo-EM images of an ensemble of biomolecules. Specifically, I used manifold embedding to elucidate metabolic function in the form of a low-dimensional energy landscape and corresponding continuum of atomic structures.
Recently, I’ve joined the Simons Center for Quantitative Biology at Cold Spring Harbor Laboratory as a Computational Postdoctoral Fellow. The research is formed in collaboration between the Kinney and Koo labs, with the goal to bridge the divide between “black-box” deep neural network models in genomics and mechanistically interpretable biophysical models of gene regulation.
Almost a decade ago, previous to my scientific endeavors, my profession was in the arts (specifically 2D and 3D animation and design). Although my path has changed, I still love to design and find ways to incorporate those skills into my scientific work. As for me personally, I enjoy learning new things and sharing my ideas and experiences with others. In my free time, I have fun hiking, bicycling, playing sports like tennis, and team-based computer games.
This website provides an overview of my work in science and education. For more information, download my curriculum vitae
PhD in Computational Biophysics, 2022
MPhil in Biological Sciences, 2020
MA in Biological Sciences, 2019
BS in Physics, 2017
Georgia Institute of Technology
BA in Mass Communication, 2009
Python, Bash, LaTeX, git
Chimera, PyMOL, VMD, RELION, Prism
Adobe CS, Cinema4D, Final Cut Pro