Michael C. Burl

Michael C. Burl is a Principal Member of the Technical Staff at the Jet Propulsion Laboratory in the Machine Learning and Instrument Autonomy Group. He received the Ph.D. in electrical engineering from Caltech in 1997. He is well known for his work in applied machine learning, computer vision, and data mining. Among his accomplishments, he developed the Rockster rock detection and segmentation algorithm currently running onboard the Mars Opportunity rover as part of AEGIS (Autonomous Exploration for Gathering Increased Science); he was the PI for the Adaptive Sky sensor web/data fusion project; he has architected large-scale learning-based systems for locating and cataloging geological features in planetary image sets; he was a key early contributor to the Autonomous Sciencecraft Experiment demonstrated onboard EO-1 under NASA's New Millennium program; and he laid the foundation (with P. Perona and later colleagues) for the constellation model, now widely used in object recognition. He has served as a Vice Chair for the SIAM Data Mining Conference, as well as on the Program Committees of many top-tier data mining and computer vision conferences.