Alexander Schell

I am currently a postdoctoral researcher at the Seminar for Applied Mathematics at the Swiss Federal Institute of Technology in Zurich. 

My research focuses on probabilistic and statistical machine learning, mathematical statistics, stochastic analysis, and applied analysis.
I am particularly interested in stochastic dynamics, statistical inverse problems, and inference from multidimensional stochastic processes, and my work frequently uses rough paths theory to bridge these areas. I am especially drawn to research at the intersection of machine learning and stochastic analysis, where I aim to combine diverse mathematical concepts and techniques to address statistical problems with substantial practical applications.  

Previously, I was a postdoctoral researcher at the Department of Statistics at Columbia University. I am also an associate member of the DataSıg Research Group. I received my PhD in Mathematics from the University of Oxford in autumn 2022, under the supervision of Harald Oberhauser. Prior to this, I completed an MSc in Pure Mathematics at Imperial College London and a BSc and MSc in Mathematics with a minor in Theoretical Physics at Ulm University in Germany.

A detailed CV is available on request.