I am an Aeronautics PhD student at Imperial College London, part of the Computational Astrodynamics (COAST) group. My research focuses on autonomous sensing and tracking of Low Earth Orbit (LEO) satellites under severe uncertainty 🛰️.
My research interests span orbit determination (OD), uncertainty quantification (UQ), machine learning (ML), and space exploration. I am particularly interested in developing computational frameworks that solve challenging scientific and engineering problems.
Developed mlbiosig, an interpretable ML framework for distinguishing between biological and non-biological py-GC-MS chemical samples in icy ocean world environments, in support of NASA's Europa Clipper-MASPEX instrument.
Publication: Rajpoot, G. M. Z., et al. (2026). From Mass Spectra to Biosignatures: Interpretable Machine Learning for Life Detection on Icy Ocean Worlds. NeurIPS 2026 Interp4Discovery Workshop.
Research interests: Machine learning · Explainable AI · SHAP · Astrobiology · Biosignature detection
Developed astrotrack, a Python package for characterising LEO satellite interference in radio observations using TLE/SGP4 propagation and site geometry, in support of the Cambridge-led REACH experiment in South Africa.
Publication: Rajpoot, G. M. Z., et al. astrotrack: Characterising LEO Satellite Interference in Wide-Field Radio Astronomy. RAS Techniques & Instruments (in preparation).
Research interests: Satellite tracking · Radio astronomy · Radio-frequency interference · Orbital mechanics
I would love to connect with researchers and industry experts working in the field, so feel free to reach out!
- GitHub: @Gabriella8080
- LinkedIn: Gabriella Rajpoot
