Dr. Yuliya Marchetti is a data scientist in the Machine Learning and Instrument Autonomy group at JPL. During her tenure, she contributed various statistical and machine learning systems, including ML-based onboard bad pixel identification for Orbiting Carbon Observatory-2 and -3; autonomous terrain detection for Barefoot Rover, a tactile wheel concept for exploratory rovers; ML modeling for targeted science observations; and explainable ML framework for science interpretation of bias in physics-based model data. She has served as an onboard data analytics and science value implementation lead for the Europa Lander Autonomy System prototype. Her current projects include on ML-based analysis of hyperspectral imaging spectroscopy data from Earth Surface Mineral Dust Source Investigation (EMIT) and deep learning modeling of multivariate time series for applications in navigation and communications, instrument health monitoring and engineering data.

Previously, she has worked at JPL as a postdoctoral scholar on developing spatiotemporal modeling and fusion methods for massive sea surface datasets. Yuliya received her Ph.D. in Statistics and Applied Math from University of California, Los Angeles.

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Education

• Statistics (PhD) - University of California, Los Angeles

Research Interests

• Machine Learning & Deep Learning
• Temporal data and signal processing
• Ground mission operations
• Imaging Spectroscopy