Nathan Sauldubois
Postdoctoral researcher in applied mathematics at NYU Tandon School of Engineering, working in probability, optimal transport, martingale optimal transport, and model risk.
I received my Ph.D. in Applied Mathematics from École Polytechnique under the supervision of Nizar Touzi and defended my dissertation on November 25, 2025. My research lies at the intersection of probability theory, stochastic calculus, optimal transport, and distributionally robust optimization. I am particularly interested in Wasserstein and adapted Wasserstein distances, martingale optimal transport, Wasserstein gradient flows, and their applications to mathematical finance and stochastic control.
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