The Varner Lab builds mathematical models and computational tools at the intersection of engineering, data science, and applied mathematics — spanning quantitative finance and machine learning today, on a deep foundation in systems and synthetic biology.
A consistent toolkit — mechanistic modeling, ensemble parameter estimation, and machine learning — applied to systems as different as a financial market and a living cell.
Methods from engineering, statistics, and machine learning applied to financial systems — agent-based market simulations, transformer models for financial time series, and regime-aware models of risk and return.
Two decades building predictive, mechanistic models of biological systems — metabolic networks, signal transduction, the coagulation and complement cascades, and cell-free protein synthesis.
Peer-reviewed articles and preprints, 1997–present, with links to code and data.
Browse →Open-source packages and models for finance, simulation, and computational biology.
Browse →Courses in computational thinking, machine learning, and quantitative finance.
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