Amy Braverman is Principal Statistician at the Jet Propulsion Laboratory. She specializes in the development of new statistical methods for massive data sets, particularly remote-sensing data collected for Earth and Climate Science. She is a Fellow of the American Statistical Association, is a member of several different mission teams at JPL, and the PI of NASA-funded research projects on spatio-temporal data fusion and climate model evaluation using observations.

Julian Bunn is a Principal Computational Scientist in the Center for Data Driven Discovery at Caltech. He is a member of the CMS collaboration at CERN, and a Fellow of the Institute of Physics. His current interests include distributed event based systems and machine learning.

Daniel J. Crichton is a program manager and principal computer scientist at NASA JPL.  He is the Director of the Center for Data Science and Technology and is actively involved in leading the development of several data intensive systems for planetary, Earth Science, and biology. His interest areas include novel software architectures and methods for distributed data management and analysis.

Scott Davidoff leads design and development of human interfaces for mission operations at NASA’s Jet Propulsion Laboratory. He investigates how Data Visualization and Virtual Reality impact space exploration and tele-robotics, and is a NASA and Caltech Principal Investigator.

S. George Djorgovski is a Professor of Astronomy at Caltech, and is interested in data intensive science in general, especially the methodology and commonalities between different disciplines.  He was one of the founders of the Virtual Observatory framework, and the emerging discipline of Astroinformatics, and a PI of several large digital sky surveys.

Ciro Donalek is a Computational Staff Scientist at Caltech. His interests include machine learning and immersive and collaborative scientific data visualization, and their application to Astronomy, Biology and other scientific fields.

Richard Doyle is the Program Manager, Information and Data Science at JPL. His interests include data science / informatics, autonomous systems, flight- and ground-based computing, smart instruments, cyber-security and space asset protection, and related topics.

Thomas Fuchs is a Research Technologist at JPL. His research interests include development of new statistical learning algorithms and their application in computer vision, astronomy, computational pathology, and robotics.

Matthew Graham is a Senior Computational Scientist at Caltech, and is interested in the application of advanced computer science and statistics methodologies to data intensive science problems, particularly in astronomy. He has been heavily involved in both national and international Virtual Observatory efforts and in the statistical characterization of large digital sky surveys.

Ashish Mahabal is a Senior Research Scientist in Astronomy at Caltech. He is interested in astronomical transients and has worked on several sky surveys and is the co-chair of the LSST Transients and Variable Stars group. He works on Big Data, data fusion, machine learning and real-time classification of anomalies.

Chris Mattmann is the Chief Architect in the Instrument and Data Systems section at JPL, an Adjunct Associate Professor in the Computer Science Department at USC, and a Director at the Apache Software Foundation. The overarching theme of his research is the design of large-scale, distributed, data intensive systems.

David R. Thompson is a research technologist at the Jet Propulsion Laboratory, California Institute of Technology.  He is PI of multiple NASA projects applying machine learning principles to spacecraft autonomy.  His algorithms have guided autonomous robots and sensors fielded to North America, South America, the Atlantic Ocean, Airborne demonstrations, Low Earth Orbit, and the surface of Mars.