My name is Evan Seitz and I’m currently a Computational Postdoctoral Fellow in the Simons Center for Quantitative Biology at Cold Spring Harbor Laboratory. In this role, I’ve developed advanced interpretation techniques to understand gene-regulatory mechanisms learned by black-box deep neural networks.
Previously, I obtained my doctorate at Columbia University working on Computational Biophysics in the Frank Lab. My thesis work focused on the development, interpretation and refinement of a geometric machine-learning approach to elucidate metabolic function in the form of a low-dimensional energy landscape and corresponding continuum of atomic structures.
A commonality in my work is the navigation of biological complexity through the application of machine learning models augmented by advanced interpretation techniques.
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. I also love 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 video 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
Columbia University
MPhil in Biological Sciences, 2020
Columbia University
MA in Biological Sciences, 2019
Columbia University
BS in Physics, 2017
Georgia Institute of Technology
BA in Mass Communication, 2009
Georgia College