FDL-X Heliolab is a prestigious summer program, focusing on the application of physics-informed machine learning to heliophysics. Responsibilities include collaborating with top-tier academic and commercial AI partners to enhance predictive models for space weather phenomena. The program involves an intensive 8-week research sprint, culminating in a Technical Showcase, demonstrating advancements in geoeffectiveness continuous learning. Engaged in full-time research with global experts, contributing to groundbreaking developments in AI and space science.

This position emphasizes the use of computer science, machine learning, open source code development (e.g. PyHC heliopython.org), cloud computing (through the AWS HelioCloud), and advanced statistical methods to expand the discovery potential of heliophysics mission data, theoretical models, and simulations.

Used python to find statistical relationships between solar flares, coronal mass ejections and their associated solar energetic particles