NASA Space Apps Challenge

// Overview

NASA's DSCOVR satellite sits at the L1 Lagrange point and streams measurements used to monitor space weather. The challenge: extract meaningful signal from that data stream using machine learning, under the time pressure of the NASA Space Apps hackathon.

Working remotely with a small team, I developed a Python-based machine-learning algorithm to analyze the DSCOVR dataset, building the full pipeline from raw data to model output within the event window.

// What I did

• Explored and cleaned the DSCOVR and ACE satellite datasets (2016–2020).
• Engineered features relevant to the space-weather signal.
• Built and trained a Python machine-learning model to predict IMF components.
• Evaluated results and presented within the hackathon window.