Rohan Sen

Rohan Sen is a PhD Assistant at the Faculty of Economic Sciences, University of Italian Switzerland (USI), affiliated with the Institute of Finance (IFin). His research focuses on kernel methods, statistical learning theory, econometrics, and explainability, with expertise in mathematical finance and statistics. He holds a Master's in Mathematics and Computing from IIT Guwahati (2019) and is pursuing his PhD under Prof. Paul Schneider and Prof. Michael Multerer.

Research interests include kernel-based methods for moment problems, financial econometrics, and explainable AI. Recent work addresses observation-specific explanations via scattered data approximation and fast empirical scenarios in computational finance. He actively contributes to conferences like the World Conference on Explainable AI and FinEML.

No scientific awards are listed. His professional experience includes a stint as a Senior Software Engineer at HCL Technologies (2019-2020). He has participated in workshops on decision-making under uncertainty and advanced C++ programming. Current activities involve probabilistic energy forecasting and kernel-based quantile regression.