April 2024
Building a company. Building conviction.
A conversation about AI Squared, entrepreneurship, and the relationships behind a $13.8 million funding round.
Read the Forbes featureBuilding AI Squared. The story behind the company.
Genetic variation and the plasma proteome across ancestry groups.
AI Squared’s $6 million seed round and the path to everyday AI.
Inside the AI boom on Closing Bell Overtime.
Individual and community-level risk for COVID-19 mortality in the United States.
Code, consequences, and the ethics of AI.
AI Squared named among the 10 hottest AI startups of 2022.
The entrepreneur behind AI Squared’s $13.8 million round.
Four current areas, connected by a question:
how do we make powerful systems trustworthy and useful?
Can AI agents maintain authorized behavior as incentives, context, and pressure change?
Research, contributions & chronologyCan expert-grounded attribution and traceable rights evidence protect IP while keeping legitimate work usable?
Research, contributions & chronologyOn building companies, putting AI to work,
and the possibilities ahead.
From cloud-scale genomics to population health.
Read the original work. Follow the evidence.
5 publications
Nature Genetics
Connecting genetic variation and the plasma proteome across ancestry groups to support proteome-wide association studies.
J. Zhang, D. Dutta, A. Köttgen, A. Tin, P. Schlosser, M. Grams, B. Harvey, B. Yu, E. Boerwinkle, J. Coresh, N. Chatterjee & the CKDGen Consortium
Nature Genetics · 54, 593–602 · 10.1038/s41588-022-01051-w
Nature Medicine
A framework for understanding how individual risk and community context shape COVID-19 mortality risk.
J. Jin, N. Agarwala, P. Kundu, B. Harvey, Y. Zhang, E. Wallace & N. Chatterjee
Nature Medicine · 27, 264–269 · Published online December 2020 · 10.1038/s41591-020-01191-8
IEEE Journal of Biomedical and Health Informatics
Using scalable computing to make large-scale cancer genomic analysis more practical.
Benjamin Simeon Harvey & Soo-Yeon Ji
IEEE Journal of Biomedical and Health Informatics · 21(1) · First published online in 2015 · 10.1109/JBHI.2015.2496323
IEEE EMBC
Exploring cloud-scale classification methods for gene expression microarray data.
Benjamin Harvey & Soo-Yeon Ji
IEEE EMBC · Proceedings, 7152–7155 · 10.1109/EMBC.2014.6943968
IJISET / arXiv
A comparative review of three approaches to parallel computation and their implementation tradeoffs.
Kato Mivule, Benjamin Harvey, Crystal Cobb & Hoda El Sayed
IJISET / arXiv · IJISET 1(8), 208–217 · arXiv:1410.4453
Publication years follow the journal issue; earlier online dates are noted. This collection brings together the publications identified in my research record.
Different environments.
The same drive to make an idea useful.
Computer science at Mississippi Valley State and Bowie State. Bioinformatics research training through Harvard–MIT Health Sciences and Technology, followed by work at Brigham and Women’s Hospital and the NIH.
Building the teams and technology
to move important work forward.
Bringing AI into the applications and workflows where people already work.
A home for turning ambitious AI ideas into companies and useful systems.
Connecting technology and the people responsible for delivering on a mission.
Exploring AI systems designed around purposeful, human-directed work.
How my work through Spyris, Archetypal, and NSA technology collaboration connects to the research I want to pursue at GW.
Three connections across genomics, population health, and the systems that bring research into practice.
Useful AI needs more than a prediction. It needs a place in the work.
Research collaborations. Speaking. Building something that matters.