Please join CPAESS for a virtual seminar talk with Dr. Prateek Mayank. Dr. Prateek Mayank is a NASA Jack Eddy Postdoctoral Fellow at Univ. of Colorado, Boulder, working on space weather drivers using physics-based modeling and machine learning methods. He received his Ph.D. from IIT Indore (India) in 2024, where he developed SWASTi framework (MHD model of the solar wind and CME). He is also recipient of Justice Oak Outstanding Thesis Award, given by Astronomical Society of India. His current research focuses on physics-enabled AI frameworks that enhance observation-driven inputs and develop surrogate models for operational forecasting.
How AI is Transforming Solar Wind Research and Forecasting
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Wednesday, August 19, 2026 at 11:00am MT (Virtual)
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SUMMARY: Our Sun, while sustaining life on Earth, also constantly erupts streams of charged particles and bursts of plasma that fill the solar system and shape the space around Earth. These high energy events, known as space weather, can damage satellites, disturb power grids, and interrupt navigation and communication systems. However, forecasting these events accurately and in a timely manner remains a significant challenge. While simple empirical models are fast, they offer limited insight. Conversely, detailed physics-based simulations are accurate but too slow for real-time forecasting. Artificial intelligence is breaking this deadlock by integrating both approaches into an explainable learning pipeline.
In this talk, I will demonstrate how deep learning is advancing the forecasting of space weather drivers, particularly solar wind. By incorporating system information into the choice of architecture and training curriculum, these models provide significant enhancements in accuracy and generalizability. Additionally, feature attribution methods help clarify/discover which factors truly drive an event. I will also showcase how physics-informed neural operators can effectively emulate MHD solutions, accelerating heavy simulations from hours to seconds while maintaining physical fidelity.
For more information, visit the CPAESS Discovery Seminars page
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Alex Meyer
Graphic Artist II, CPAESS
UCAR, UCP and NSF NCAR
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