The Machine Learning and Instrument Autonomy strives to research, develop, and infuse machine learning and other data science supporting technologies to advance robotic exploration and science.
Recent News
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▸ July 3rd, 2025 by Jake Lee
Jake Lee, Michael Kiper, David Thompson, and Phil Brodrick published in the Proceedings of the National Academy of the Sciences (PNAS) a new deep learning model, SpecTf, for cloud detection in imaging spectroscopy data. SpecTf leverages a spectroscopy-specific transformer architecture to generate high-accuracy cloud masks, significantly outperforming the current EMIT baseline. Notably, SpecTf requires only spectral information, demonstrating strong performance and interpretability through its attention mechanism, revealing physically meaningful spectral features. The model also exhibits potential for cross-instrument generalization. The resulting cloud mask will be deployed as a new EMIT product.
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▸ June 11th, 2025 by Ryan McGranaghan
Ryan McGranaghan planned, convened, and hosted a first-of-its-kind event on June 9th titled “Boston-Area Complex Risk Science: Exploring new frontiers and a new community for understanding risk.” Held at Northeastern University, it gathered 40 individuals from across the Boston area to identify non-obvious gaps in risk science, particularly around multi-hazard interactions, cascading consequences, and vulnerability, and to explore how complexity science and social science can help us understand and address them. Institutions involved included MIT Lincoln Laboratory, the MIT Media Lab, Harvard, NASA Lifelines, the Electric Power Research Institute, New England Independent System Operator (NE-ISO), Dartmouth University, the Massachusetts Clean Energy Center, among many others.
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▸ June 11th, 2025 by Mario Damiano
ExoReL (Exoplanet Reflected Light retrieval), a Bayesian inverse retrieval framework used to interpret exoplanetary reflected light spectra, has been open sourced by PI and developer Mario Damiano. ExoReL has been instrumental in supporting research related to the Habitable World Observatory and the Starshade probe, appearing in over eight peer-reviewed journal articles. Researchers will also utilize ExoReL to analyze upcoming data from the Roman Space Telescope, specifically reflected light spectra of cold gaseous giant planets.
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▸ June 4th, 2025 by Yuliya Marchetti
Recent research led by Joseph Bowkett and co-authored by Yuliya Marchetti, published in Science Robotics, details a successful field demonstration of fully autonomous surface sampling technologies for a future Europa Lander mission. The work, conducted on the Matanuska Glacier in Alaska, showcases a hardware and software prototype capable of navigating the challenges of Europa’s unknown surface conditions, limited communication windows, and harsh environment – key steps towards searching for potential life on Jupiter’s icy moon.