This project aims to advance the detection of lethal, non-trackable space debris (10 μm-10 mm) by analyzing non-thermal electromagnetic (NTEM) radiation emitted during hypervelocity collisions. We will leverage AI/ML models to automatically identify and classify these collision signatures using observational data from ground-based radio telescopes, thereby improving the efficiency of debris monitoring.
- Science Mentor: Mojtaba Akhavan-Tafti, Climate and Space Sciences and Engineering, College of Engineering
- AI Mentor: Yang Chen, Statistics, LSA