Jan Obloj

I have a general interest in mathematics of randomness. Most of my research sits at the crossroads of various fields, including: probability theory, statistics, mathematical finance, operations research, optimal transport and data science. A lot of my research is related to problems in mathematical finance and my main focus is on robustness of the modelling pathways from input out outputs, ways to understand and quantify it. My research spans the spectrum from theoretical foundations of robust pricing and hedging paradigm in mathematical finance, to practical questions of building fast generic ways to approximate adversarial robustness of deep neural networks. A significant part of my recent research involves techniques from optimal transport (OT), in particular in relation to the martingale OT problem and adapted OT, as I find these problems endlessly fascinating and beautiful.

With M. Hasenbichler, B. Joseph, G. Loeper and G. Pammer, The Martingale Sinkhorn Algorithm, 2025. With I. Guo, Robust Pricing and Hedging of American Options in Continuous Time, 2025. with Y. Jiang, Sensitivity of causal distributionally robust optimization, 2024.