Ryan McCorvie
From stochastic theory
to production systems.
Mathematician and statistician bringing rigorous probabilistic thinking to machine learning and AI.
About
I'm a mathematician and statistician based in Oakland, California. My academic training is in probability theory and stochastic processes — I did graduate work at UC Berkeley under Steven Evans and Lisa Goldberg, focusing on Hawkes processes, point processes, and high-dimensional statistical learning. My undergraduate degree is in mathematics from Caltech.
I spent 13 years as a quantitative analyst at Goldman Sachs, where I managed the PhD team responsible for modeling corporate bankruptcies during the 2008 credit crisis. I also contributed to establishing the ISDA standard CDS model — the industry reference for credit default swap pricing.
Through Martingale AI I've applied this background to public health, working with the California Department of Public Health on COVID-19 modeling that resulted in peer-reviewed publications in Health Affairs, IJERPH, and Frontiers in Public Health. My current focus is the intersection of probabilistic methods and modern AI — including formal verification and the mathematical foundations that make AI systems more reliable and interpretable.
Selected Work
COVID-19 Statistical Modeling — California Dept. of Public Health
Statistical consulting for the California Department of Public Health contributing to three peer-reviewed studies: analysis of racial and ethnic disparities in COVID-19 exposure and case rates (co-authored with CDPH and Stanford), school testing policy risk tradeoffs (co-authored with CDPH and UCSF), and technical design of CalCAT, the state's long-running COVID forecast aggregation dashboard.
Goldman Sachs — Quantitative Analysis
Thirteen years as a quantitative analyst ("strat") at Goldman Sachs. Managed the team of PhD analysts responsible for bankruptcy and credit modeling during the 2008 financial crisis. Principal contributor to the establishment of the ISDA standard CDS model, the industry reference for credit default swap pricing that standardized the global derivatives market.
Probabilistic Methods and Formal Mathematics
Graduate research at UC Berkeley in stochastic processes, including Hawkes processes, Gaussian process methods, and point process theory. Currently participating in a working group formalizing stochastic calculus in Lean. Expository notes on diffusions and PDEs, branching processes, lace expansions, and the Karlin-McGregor theorem are on my academic page.
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