Meeting roles in:
AI Foundation Models for Observational and Gridded Data Across Scales
MeltwaterBench: Deep learning for spatiotemporal downscaling of surface meltwater
Advances in Emulating Earth System Models I Poster
Advances in Emulating Earth System Models II Oral
Advancing Emulation for Understanding Nature-Society Interactions
Hello, I am a postdoctoral associate in the MIT Department of Earth, Atmospheric, and Planetary Sciences. My research is tackling climate change with machine learning, little-by-little, together with Prof. Raffaele Ferrari and Prof. Noelle Selin.

I am concerned that running a high-resolution (1km) climate model can take multiple weeks on the world's largest supercomputers; consuming the same electricity a coal power plant would generate in one hour. To overcome the computational complexity, we are reshaping machine learning models into fast copies, or 'surrogates', of climate models. The core difficulty is to ensure physical-consistency in the surrogates, such that policy- or decision-makers can trust the machine learning surrogates.