Developed and tested mmWave radar algorithms and AI-based signal processing pipeline that improved data interpretability, enabling more accurate atmospheric sensing from raw observations
Validated the system’s performance through rigorous testing, ensuring the algorithms could accurately capture key environmental patterns
Astrophysics Research Intern
University of San Francisco
San Francisco, CA
01.2025 - 03.2025
Used dimensionality reduction and clustering techniques to cut through high-dimensional data and reveal meaningful relationships between local and distant galaxies
Strengthened the foundation of the research by conducting deep literature reviews, ensuring the analytical approach was grounded in established astrophysical knowledge
Education
Master of Science - Environmental Economics And Policy & Nuclear Engineering