Bryan Matthews received his Bachelor’s Degree in Electrical Engineering from Santa Clara University in 2002. Since 2001 he has worked at NASA Ames Research Centre 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 applied machine learning algorithms to gather insights into complex engineered systems. 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 Centre, Bryan supports the development, testing, and deployment of anomaly detection algorithms that target the discovery of unknown operational safety events in the national airspace. 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 collaborates with both domestic and international partnerships in industry, as well as other government agencies where he utilises advanced algorithms to intelligently mine heterogeneous data sources to ultimately improve the safety and efficiency of air travel.