James Montgomery is a data scientist with the Machine Learning and Instrument Autonomy group of the Jet Propulsion Laboratory (JPL). Specializing in ML engineering and software development, James contributes to the advancement of research through improving the quality of the products developed by the group in efforts to infuse these products with other technologies and missions across JPL.

Prior to JPL, James indirectly supported the research of JPL by working under the Jim Bell Research Group of Arizona State University. After having caught the interest of JPL through his efforts with ASU, James went on to finish his bachelor’s degree in Computer Science and refocus his energy into the future of JPL.

During his time at JPL, James has contributed to the development of many open source projects:

• ISOFIT - A set of routines and utilities for fitting surface, atmosphere and instrument models to imaging spectrometer data.
• ISOFIT-Tutorials - Tutorials and examples for ISOFIT.
• ISOFIT-Data - Additional data dependencies for ISOFIT.
• ISOFIT-Plots - Command-line and browser-based visualizations tools for ISOFIT.
• Mined-Lands - Leverages EMIT products to investigate the presence and future risk of acid mine drainage.
• SUDSAQ - Research pipeline to explain the subscale drivers of air quality pollution as part of Science Understanding through Data Science.
• TimeFED -A machine learning system for Time series Forecasting, Evaluation and Deployment that supports both classical and deep learning models.
• mlky - A flexible configuration management package to reduce implementation costs and adapt to scales small and large for research projects at JPL

Find my publications on Google Scholar

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Education

• Computer Science (BS) - Arizona State University

Research Interests

• Generalizable Machine Learning
• Data systems scaling
• ML explainability
• ML engineering