Summary
Bedartha Goswami is an Assistant Professor and former group leader with a decade of experience advancing machine learning applications in climate science. Trained at IISER Pune and with a PhD from the Potsdam Institute for Climate Impact Research, he blends nonlinear dynamics, Bayesian inference, and time-series methods to extract low-dimensional representations of climate variability. He led an independent research group at the University of Tübingen focused on data-driven subseasonal-to-seasonal weather prediction, translating theoretical approaches into operationally relevant models. His work sits at the intersection of rigorous dynamical systems thinking and modern ML, emphasizing principled, interpretable models rather than black-box forecasting. Based in Pune, he brings a rare mix of deep physics training and hands-on data-science leadership to academic and applied climate challenges.
10 years of coding experience
5 years of employment as a software developer
Bachelor of Science - BS, Bachelor of Science - BS at Indian Institute of Science Education and Research (IISER), Pune
Dr. rer. nat. Climate Physics, Dr. rer. nat. Climate Physics at University of Potsdam