Bryan Matthews | Research Engineer - KBR, Inc.
NASA

Mr. Bryan Matthews is a senior research engineer with KBR, Inc. and member of the Data Science Group at NASA Ames Research Center. He received his Bachelor’s Degree in Electrical Engineering from Santa Clara University in 2002. Since 2001 he has worked at NASA Ames Research Center, and has been a member of the Data Sciences Group since 2005, where he has applied his professional experience in the field of data mining and machine learning.  Throughout his career, he has supported projects within NASA’s Aeronautic, Human Space Exploration, and Science Mission Directorates, where he has utilized machine learning algorithms to gather insights into complex engineered systems. He has participated in various Data Science activities at NASA including work with the NASA Engineering and Safety Center (NESC) to assistance the flight readiness review for Space Shuttle flight STS-119 and Hubble Space Telescope Attitude Observer Anomaly study.  He has a number of publications in the top data mining conferences and AIAA journals as well as in aeronautical application conferences. As a member of the Data Science Group at NASA Ames Research Center, Bryan supports the development, testing, and deployment of anomaly detection algorithms that target the discovery of unknown vulnerabilities that pose operational safety significance to the national airspace. He has overseen the open sourcing of a number of algorithms that identify anomalous events in heterogeneous timeseries data. His expertise includes working knowledge in Big Data applications, parallel computing, multiple kernel approaches, deep learning methods, regression techniques, clustering, anomaly detection, classification, time series analysis, and causal factor discovery. He manages collaborations with both domestic and international partnerships in industry, as well as other government agencies where he leverages advanced algorithms to intelligently mine heterogeneous data sources to ultimately improve the safety and efficiency of air travel.