I’m Evan Seitz, a computational biologist working at the intersection of machine learning, regulatory genomics, and structural biology. I recently joined InstaDeep as a Research Scientist, where I focus on advancing genomics using genomic large language models (gLMs) and other AI-driven approaches.

As a postdoctoral fellow at Cold Spring Harbor Laboratory with Drs. Peter Koo and Justin Kinney, I developed two explainable AI frameworks—SQUID and SEAM—for uncovering cis-regulatory mechanisms in genomic deep neural networks. Previously, I completed my Ph.D. with Nobel laureate Joachim Frank at Columbia University, where I developed geometric machine learning and explainability frameworks, including ESPER, to reveal conformational heterogeneity in cryo-EM protein structures.

My work is driven by a deep curiosity about nature, and how to leverage learning systems to extract meaning from biological complexity. I’m always open to conversations around research, collaboration, or industry roles at the intersection of AI and biology.

This site serves as a hub for my work, ideas, and ongoing projects in computational biology and machine learning. You can download my:

• 📄 Academic CV
• 💼 Industry CV

Or connect with me on LinkedIn.