Brianna Maze - Machine Learning Engineer at NextGen Federal Systems

Principal Machine Learning and Computer Vision Engineer at NextGen Federal Systems

In Fall 2023, Brianna Maze spoke with AIWVU about her work as Principal Machine Learning and Computer Vision Engineer at NextGen Federal Systems. She gave an in depth look at some of her work including research on deep learning based weather prediction, facial recognition in the wild, and model bias.

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Ms. Brianna Maze is a research engineer with over 10 years of ML experience applying SOTA techniques across challenging problem sets. She has planned and performed data collection efforts to create surveillance and multi-domain databases for facial recognition applications. She was the data development lead on the IARPA Janus Project with a deep understanding of the importance of operational data and metrics. At NextGen, she is a Principal ML engineering, managing projects and a team of ML engineers. She leads multiple programs, many of which focus on translating academic models into operational models. She oversaw the Predictive Maintenance IR&D project, applying time-series modeling to predict system failures, and has contributed ML expertise to a variety of programs to include space-weather and object detecting and tracking on-board UAVs. She has publications in the facial recognition domain, and has given invited talks and demos at various conferences and events, including the NIST International Face Performance Conference, UKMet Unified Model Data Science Session, Cyber Electromagnetic Activity meeting, and the American Meteorological Society Annual Meeting. She received her BS in Computer Engineering and her MS in Electrical Engineering, both from West Virginia University.