In this talk, I will give an overview of our efforts to mine flight operations and trajectory data to look for previously-unknown safety issues and precursors to known safety issues. I will describe some of our results, the nature of our algorithms, and plans for expanding the scope of our work.
Mining Aircraft Data for Aircraft Safety
Nikunj Oza is the leader of the Data Sciences Group at NASA Ames Research Center. He also leads a NASA project team, which applies data mining to aviation safety and operations problems. Dr. Oza's 50+ research papers represent his research interests, which include data mining, machine learning, anomaly detection, and their applications to Aeronautics and Earth Science. He received the Arch T. Colwell Award for co-authoring one of the five most innovative technical papers selected from 3300+ SAE technical papers in 2005. His data mining team received the 2010 NASA Aeronautics Research Mission Directorate Associate Administrator¹s Award for best technology achievements by a team. He is an Associate Editor for the peer-reviewed journal Information Fusion (Elsevier) and has served as organizer, senior program committee member, and program committee member of several data mining and machine learning conferences. He received his B.S. in Mathematics with Computer Science from MIT in 1994, and M.S. (in 1998) and Ph.D. (in 2001) in Computer Science from the University of California at Berkeley.