President & CEO, Co-founder
Medical technology entrepreneur. Formerly management consultant at Monitor Group, focused on medtech commercialization, and Senior VP of Marketing & Strategy at ConforMIS. BA from Harvard and MBA from Harvard Business School.
Computational biologist with expertise in genomics and machine learning. After MIT Physics undergrad, earned Harvard Applied Math PhD developing theory and computational methods for analyzing biological systems and large genomic datasets.
Infectious Disease physician at Mass. General Hospital (MGH), Assistant Professor at Harvard Medical School and a Director of Clinical Research at the Ragon Institute of MGH, MIT and Harvard. Expertise in the microbiome and its effect on immune response.
Clinical Pathology resident at MGH with expertise in immunology, the human microbiome, and diagnostics. After biomedical engineering degree at MIT, studied immunology on a Rhodes Scholarship in Oxford, and worked in Doug Kwon’s lab through the Harvard MD-PhD Program.
Senior Research Scientist at Google Brain, software engineer with a background in physics and machine learning. In his PhD at Harvard, Dougal worked on Bayesian methods and deep learning, and developed Autograd, a popular machine learning library.
Biochemist with expertise in transcriptional regulation and method development. During his PhD in the Tjian lab at UC Berkeley, Kevin developed methods to study protein-DNA interactions and identified novel histone gene regulators in Drosophila.
Full stack data scientist with experience building and scaling machine learning systems. After graduating from Harvard with a degree in statistics, Elliott designed and implemented algorithms at Firecracker to improve medical education and helped steer Firecracker to an acquisition.
As an undergraduate at Iowa State University, Febriana worked in a plant metabolism lab and completed her studies in biochemistry.
Manager, Sequencing Technologies
Sequencing aficionado with expertise in microbial ecology. After completing his bachelor's in Molecular Environmental Biology at UC Berkeley, Ian studied a variety of microbial communities and then managed the sequencing core at University of Alaska, Fairbanks.
Research Scientist, Machine Learning
Machine learning expert with background in algorithmic development, especially in the context of novel, noisy data. During his PhD in Physics at Harvard, Jae developed and implemented several scalable and robust machine learning and statistical inference techniques for a large international astronomical survey.
After studying Neuroscience at Bucknell University, Michael earned his Masters in Neurochemistry from Stockholm University where he studied the effects of post-translational modifications on cellular localization and protein interactions.
Director, Product Development
Molecular microbiologist with expertise in bacterial physiology and genetics. Nicole's post-doc at MIT focused on bacterial biofilms, and she later contributed as a technical lead to the development of a rapid pathogen identification assay at Draper Labs.
Nidhi obtained her undergraduate and Masters degrees in microbiology at the University of Manitoba in Canada, where she studied plant bacteria mutants by building cDNA libraries and conducting transcriptomic analyses.
Rachel studied Human Evolutionary Biology as an undergraduate at Harvard, and performed computational human body modeling and driver behavior research at the University of Michigan.