Onkar Jadhav

I am a research fellow at the Oceans Graduate School, where I develop machine learning (ML) frameworks for oceanography. My work primarily focuses on creating statistical downscaling techniques using ML for sub-seasonal and seasonal ocean temperature predictions.

Previously, I was a postdoctoral researcher at the University of Luxembourg, where I developed machine learning and reduced-order modeling frameworks for wind engineering and computational fluid dynamics (CFD) problems.

I hold a Ph.D. in applied mathematics from the Technical University of Berlin, where my thesis was a cross-disciplinary project that developed physics-assisted machine learning algorithms for high-dimensional partial differential equations. In my spare time, I am an avid reader, and I occasionally enjoy sketching.