Decoding biology with computing and machine learning
My name is Adam Riesselman, and I am a scientist that studies biology by building novel tools using statistics, machine learning, and robotics. I am currently a Staff Machine Learning Engineer at Hippo Harvest in the San Francisco Bay Area. (We grow plants with robots!)
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).
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:
Summarizing and interpreting complex organism-level phenotypes
Designing industrial robotic systems to capture phenotypic and environmental data at scale to power automated greenhouse and grower operations
Using 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.
Please reach out by sending an email to adam [DOT] riesselman [AT] gmail [DOT] com.