Matt Rasmussen
Matt Rasmussen


I am a VP of Data Engineering at insitro, where we develop data pipelines and infrastructure for machine learning and drug discovery. We are particularly interested in how to express complex scientific pipelines for heterogeneous data types (images, genomics, chemical informatics, etc), while easily tracking and sharing data provenance in a mixed research and production environment.

Previously, I was a VP of Software Engineering at Myriad Genetics working with engineering teams ranging from LIMS, Variant interpretation and reporting, Medical Billing, SRE, and Technical Program Management.

From 2013 to 2018, I was an engineer and later a Director of Software Engineering at Counsyl. Our team focused on various computational challenges in genomics: variant interpretation, disease risk calculations, automated genomic data pipelines, and applications of machine learning.

Before industry, I was a postdoc in Adam Siepel's lab at Cornell, where I worked on computational methods at the intersection of phylogenetics and population genetics.

In 2010, I finished my Ph.D. in Computer Science at MIT. My Ph.D. advisor was Manolis Kellis and I was a part of the Compbio lab. During my Ph.D., I worked on comparative genomics and phylogenomic algorithms for accurately reconstructing gene trees.

I have a M.S. in Computer Science from MIT, and a B.S. in Math and Computer Science from the University of Minnesota. I worked on visualization for clustering methods.



I maintain several open source software projects related (some more than others) to my research. My development interests are in phylogenetic software (DLCoal, SPIMAP, SPIDIR), scientific visualization (SUMMON), and note-taking for research settings (KeepNote).