Our mission is to improve the way organizations and individuals make decisions about new and existing biomarkers, and treatments.
Co-Founder | CEO
Jacqueline Buros Novik
Head of Data and Analytics
CompBio Research Fellow
Eric is an applied statistician and entrepreneur with many years of experience building and explaining statistical models in healthcare, financial services, and retail verticals. He is passionate about Bayesian inference, decision theory, and making complex models useful to decision-makers. Eric is a mentor in Columbia University’s Statistics Department and teaches graduate statistics courses at NYU Steinhardt. As a teenager, Eric was on the leading junior cycling team in Latvia.
Jacqueline has been working in biostatistics and bioinformatics for over 15 years, starting in cardiology research at the TIMI Study Group at Harvard Medical School before working in Alzheimer’s Disease genetics at Boston University and in biomarker discovery for cancer immunotherapies at the Hammer Lab. Most recently she was the Lead Biostatistician at the Institute for Next Generation Health Care at Mount Sinai. She is the author of the survivalstan package and a contributor to the rstanarm package.
Juho is a doctoral student in the Computational Systems Biology group at Alto University in Finland. His research interests include probabilistic and deep generative models, Gaussian Processes with both categorical and continuous input variables, reliable and efficient usage of numerical solvers in probabilistic models, dynamic modeling of single-cell RNA-seq data, and molecular network inference.
Professor of Statistics, Columbia University
Generable Co-Founder and Stan Developer
Dr. Stanski has served in senior executive roles as Vice President and Global Head, Quantitative Clinical Pharmacology at AstraZeneca Pharmaceuticals and Vice President and Global Head, Modeling and Simulation at Novartis Pharma AG. He was formerly a Scientific Advisor to the FDA Deputy Commissioner, where he introduced new quantitative methods into the regulatory review process for drugs and medical devices. In addition to his industry career, he served as Professor and Chairman of the Department of Anesthesiology at Stanford University's School of Medicine. He is a Professor Emeritus at Stanford.
Andrew is a professor of statistics and political science and director of the Applied Statistics Center at Columbia University. His books include Bayesian Data Analysis (with John Carlin, Hal Stern, David Dunson, Aki Vehtari, and Don Rubin), Teaching Statistics: A Bag of Tricks (with Deb Nolan), Data Analysis Using Regression and Multilevel/Hierarchical Models (with Jennifer Hill), Red State, Blue State, Rich State, Poor State: Why Americans Vote the Way They Do (with David Park, Boris Shor, and Jeronimo Cortina), and A Quantitative Tour of the Social Sciences (co-edited with Jeronimo Cortina).
Daniel is a computational Bayesian statistician and software engineer. He is one of the early contributors to the Stan project and is still an active member of the Stan development team. Daniel was a developer of Stan’s ODE subsystem and built PKPD models including one for an FDA-approved drug. In a past life, he's put in 10,000 hours djing and spent some time working on an aircraft carrier.