PTYS/LPL Graduate Students
Saverio CambioniAstrobiology, Planetary formation, Small bodies, Machine Learning, Remote Sensing & Space Exploration
In my research, I use machine learning to streamline ground- and space-based observations and computer simulations into fast and accurate surrogate physical models. I mainly focus on formation and evolution of asteroids and their interpretation as leftover of planetary formation. I am also interested in engineering applications of machine learning for maximizing the scientific return of space missions.
- Cambioni, S., Asphaug, E., Emsenhuber, A., Gabriel, T. S. J., Furfaro, R., and Schwartz, S. R. Realistic On-The-Fly Outcomes of Planetary Collisions: Machine Learning Applied to Simulations of Giant Impacts. Accepted for publication on ApJ. PDF here
- Cambioni, S., Delbo, M., Ryan, A. J., Furfaro, R., & Asphaug, E. Constraining the Thermal Properties of Planetary Surfaces using Machine Learning: Application to Airless Bodies. Icarus, 2019. PDF here
- Rizk, B., d'Aubigny, C.D., Hergenrother, C.W., Bos, B.J., Golish, D.R., Malhotra, R., Lauretta, D.S., Butt, J., Patel, J., Fitzgibbon, M. and May, C., Bierhaus, E.B., Freund, S., Fisher, M., Cambioni, S., and other 13 authors. OSIRIS-REx low-velocity particles during outbound cruise. Advances in Space Research, 2018. PDF here
- Cambioni, S., and Malhotra, R.. The mid-plane of the Main Asteroid Belt. The Astronomical Journal 155.3: 143, 2018. PDF here
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