Building biology better

My name is Adam Riesselman, and I am a scientist that studies biology by building novel tools using statistics, machine learning, and high-performance computing. I am currently a Staff Machine Learning Engineer at Hippo Harvest in the San Francisco Bay Area.

I received my PhD in Biomedical Informatics from Harvard University in the lab of Debora Marks as a Department of Energy Computational Science Graduate Fellow, where I was named a Frederick A. Howes Scholar. I received a B.A. in Biochemistry: Cell and Molecular Biology from Drake University in Des Moines, Iowa, where was awarded the Oreon E. Scott Outstanding Senior Award.

Previously, I have worked at insitro, the Joint Genome Institute, DuPont-Pioneer (now Corteva), the Donald Danforth Plant Science Center, and with the World Food Prize at the USDA and the International Maize and Wheat Improvement Center (CIMMYT).

Motivations and interests

I strive to apply the most recent advances in machine learning to pressing problems in biology. My focus continues to revolve around aspects of building maps from genotype to phenotype:

• How do we parameterize interpretable statistical models of biology? How can aspects of both generalized linear models and variational inference be used to explain and predict complex biological systems?

• How do we summarize and interpret complex organism-level phenotypes?

• How do we use large amounts of freely-available, but disparate, genetic data for understanding biological systems, including human genetic data, protein sequences, and protein structure?

My published work can be found on Google Scholar.

Contact

Please reach out by sending an email to adam [DOT] riesselman [AT] gmail [DOT] com.