Research Interests

I am mostly interested in the interface between Applied Probability Theory, Stochastic Optimization and Optimal Transport, with applications (mainly) in Finance, Economics and Data Science.

My current work deals with:

  • Constrained optimal transport (e.g. martingale and causal optimal transport) as a theoretical tool and as a modeling paradigm in finance, economics, and statistics.

  • Stochastic optimal control, convex analysis and optimal transport, as tools to uncover new phenomena and construct new objects in probability theory and stochastic analysis.

A sample of my current projects:

  • Causal Wasserstein distances in mathematical finance

  • Bayesian learning with Wasserstein barycenters

  • Schrödinger problems, interacting particles, and quantitative estimates

  • The geometry of stochastic processes

  • Metric projection of an 'idealized' process onto a set of processes 'calibrated-to-data'