Biography

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

Interests
  • Biophysics
  • Complex Systems
  • Machine Learning
  • Algorithm Design
Education
  • 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

Projects

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Publications

A glycan gate controls opening of the SARS-CoV-2 spike protein
Nature Chemistry, 2021