Jake Lee is a data science researcher in the Machine Learning and Instrument Autonomy group at the NASA/Caltech Jet Propulsion Laboratory. After earning his bachelor’s and master’s degrees in computer science at Columbia University (‘19, ‘20), he joined JPL to continue applying state-of-the-art ML and DL methods to solve problems in the physical sciences. His current projects include the deep learning detection of methane plumes on EMIT, the calibration of weak gravitational lensing methodologies for the Euclid space telescope with deep generative models, and physics-informed ML for ion-specific electrode array signal retrieval. His past projects include onboard science instrument autonomy (OSIA) for the Ocean Worlds Life Surveyor (OWLS). He was recently a co-visiting lecturer for CS155: Machine Learning and Data Mining on behalf of Prof. Yisong Yue during 2023 Winter. Externally, he is a volunteer coach for a local FRC robotics team.

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Education

• Computer Science (BS, MS) - Columbia University

Research Interests

• Machine Learning
• Deep Learning
• Computer Vision
• Interpretable/Explainable ML
• Robust ML