Data Science & ML to Support Future Space Missions to Mars & Ocean Worlds | Victoria Da Poian
Victoria Da Poian, Data Scientist, NASA Goddard Space Flight Center presents a Technical Talk at the 2024 WiDS Worldwide, Stanford conference.
Future planetary exploration missions, such as those targeting habitability and potential life on distant bodies like Titan and Enceladus, face communication constraints with limited transfer rates and short windows. Traditional ground-in-the-loop operations are impractical for such remote targets, necessitating additional autonomy for mission success. Leveraging machine learning and data science, our research aims to enable science autonomy onboard space missions. This autonomy allows spacecraft to make scientific decisions independently, optimizing exploration efficiency and maximizing scientific returns by streamlining data collection and analysis processes, particularly in mass spectrometry data analysis. Ultimately, this approach promises to revolutionize planetary science missions by enhancing exploration capabilities and scientific outcomes.
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