Rajat Masiwal

I am a postdoctoral scholar at the University of Chicago working on improving sub-seasonal forecasting in the tropics using data-driven and AI-based emulators. My research explores how machine learning and statistical approaches can improve prediction skill on sub-seasonal timescales. In addition to that, I am working on finding better ways of benchmarking these models.

Previously, I completed my PhD at the Center for Atmospheric and Oceanic Sciences (CAOS), Indian Institute of Science (IISc), under the guidance of Dr. Ashwin Seshadri. My doctoral research focused on understanding the interaction between convection and circulation in the tropics, particularly for the high-impact synoptic systems and low-frequency intraseasonal oscillations prevalent during the Indian Monsoon. 

I also maintain an active interest in the meteorology of renewable energy resources, such as wind and solar, and how better forecasting can support a transition to a decarbonized electricity grid. 

A detailed CV can be found here.