Our mission is to change the way companies and individuals evaluate the 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.

Core Team

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Eric Novik

Founder | CEO

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Eric manages our customer engagements and user-facing product features. Before Generable, he built data products and statistical models in healthcare, financial services, and retail verticals. Eric is passionate about Bayesian inference, decision theory, and making complex models useful to decision makers. As a teenager, Eric was on the leading junior cycling team in Latvia.

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Daniel Lee

Founder | CTO

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Daniel is responsible for our high-performance statistical computing environment. Daniel is one of the early contributors to the Stan project and is still an active member of the Stan community. In a past life, he's put in 10,000 hours djing and spent a few weeks working on an aircraft carrier.

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Krzysztof Sakrejda

Senior Biostatistician

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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.

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Luka Tomasevic

Principal Software Engineer

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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.

Scientific Collaborators

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Andrew Gelman

Professor of Statistics, Columbia University

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).

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Sam Brilleman

Postdoctoral Research Fellow, Monash University in Melbourne, Australia

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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.

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Jacqueline Buros Novik

Senior Biostatistician, Icahn School of Medicine at Mount Sinai

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Jacki has been working in biostatistics and bioinformatics for over 10 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 at Mount Sinai.

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