About

I’m Evan Seitz — a computational biologist working at the interface of machine learning and genomics. My research focuses on model interpretability, particularly using deep learning to understand how DNA sequence encodes regulatory function.

I develop methods like SEAM and SQUID to uncover what these models are actually learning, from transcriptional regulation to the mechanistic effects of mutations. SEAM was recently presented at the ICLR GEM Workshop, and SQUID was published in Nature Machine Intelligence.

This blog is a space for methods, ideas, tangents, and ongoing experiments — especially those that don’t always fit neatly into a paper. For a more complete overview of my background and published work, visit my main website: evanseitz.com.