Our mission is to change the way companies and individuals evaluate and make decisions about new and existing therapies. Our team members are core developers of Stan, a popular probabilistic programming language with a large and growing user base.
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 the Columbia University’s Statistics Department and taught seminars at the Quantitative Methods in the Social Sciences (QMSS) program at Columbia. As a teenager, Eric was on the leading junior cycling team in Latvia.
Daniel is responsible for our high-performance statistical computing environment. 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.
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.
Krzysztof is leading our probabilistic modeling and methodology development. Krzysztof is also a core Stan developer making contributions to the math library and interfaces. During his academic work, Krzysztof developed survival models for partially observed wild animal populations, predictive models for the spread of dengue fever, and spatiotemporal models for demographic survey data.
Luka leads our software architecture and development of the Generable platform. Prior to Generable, Luka built a full-stack software infrastructure at Reonomy including data integration, machine learning, algorithm development, and user-facing APIs. When Luka was two years old, he programmed his mother’s toaster to make candy out of rye bread. Ask him.
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 currently serves as 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).
Sam has a keen interest in survival analysis, joint longitudinal-survival models, models for longitudinal data from cohort studies, Bayesian inference, and in the design of Bayesian adaptive clinical trials. His PhD was entitled "Joint longitudinal and time-to-event models: development, implementation and applications in health research" and was supervised by Prof Rory Wolfe (primary), Dr Margarita Moreno-Betancur, and Dr Michael Crowther.