Dr. William Jeremy Coupe is an Aerospace Engineer at NASA Ames Research Center. He was the recipient of the 2020 NASA Superior Accomplishment Award for outstanding promotion and proliferation of Artificial Intelligence and Machine Learning (AI/ML) applied to aviation and the recipient of the 2019 Aeronautics Research Mission Directorate Award in the category of High Potential.
He is currently the Lead for ATM-X Digital Information Platform (DIP) Sustainable Aviation CDDR Demo which deployed a suite of real-time Machine Learning (ML) models to help Air Traffic Controllers manage the flow of traffic at the Nation's busiest airports. The ML Airport Surface Model forms the building blocks of a cloud-based predictive engine that alerts flight operators to pre-departure Trajectory Option Set (TOS) reroute opportunities within the terminal airspace.
Previously he was the Lead for ATD-2 Machine Learning which open sourced the Machine Learning Airport Surface Model on NASA github via the NASA Open Source Agreement. The software is built in python and leverages open source libraries kedro, scikitlearn, MLFlow, and others. The software provides examples how to build three distinct pipelines for data query and save, data engineering, and data science. These pipelines enable scalable, repeatable, and maintainable development of ML models.
He received his BS degree in Mathematics from the University of San Francisco and both an MS degree in Applied Mathematics and Statistics and Ph.D. degree in Computer Engineering from the University of California, Santa Cruz where he was a member of the Robotics and Control Lab.
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