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Enabling a Data-Driven Ecosystem at NASA and JPL | SystemsThatLearn@CSAIL L...
Thu, March 23, 2017, 4:00 PM – 5:00 PM EDT
JPL and NASA have unlocked unprecedented amounts of scientific knowledge through exploration of our solar system, universe and planet Earth. The robotic spacecraft that JPL builds to support this scientific research has generated enormous amounts of data that have also challenged the traditional approaches to capturing, managing, analyzing and ultimately gaining insight from the data. Newer architectures and methodologies are needed to consider the entire observing system, from spacecraft to archive, with integrated data-driven discovery approaches. Advances in data and computational science capabilities offer opportunities to gain new insights from space missions and the vast data collections that NASA has amassed over the last fifty years. It is also clear that these advances can be worked through collaborations with academia, research, industry and the open source community. Through a joint partnership in Data Science, JPL and Caltech are working to innovate new architectures, exploit emerging technologies, develop new data-driven methodologies and transfer them across disciplines and domains, and explore approaches for interactive data visualization and analysis that can be applied across the entire mission-science data lifecycle, from deep space to data analytics.
Daniel Crichton, Program Manager, Prinicpal Investigator and Principal Computer Scientist, NASA's Jet Propulsion Laboratory (JPL)
Daniel Crichton is a program manager, principal investigator, and principal computer scientist at NASA's Jet Propulsion Laboratory, which he joined in 1995. He is the leader of the Center for Data Science and Technology, a joint center formed with Caltech, focusing on the research, development and implementation of data intensive systems for science and missions. Mr. Crichton has program management appointments to multiple JPL program offices for data science and data intensive system projects in solar system exploration, earth science, and technology for NASA and non-NASA sponsors. He manages the Planetary Data System Engineering Node, responsible for software architecture, development, and operations of a national, distributed archive system curating all the scientific data from robotic exploration of the solar system. He was one of the founding members of the International Planetary Data Alliance (IPDA), an organization committed to building compatible international planetary science data archives. He also serves as principal investigator of several distributed data system projects for NASA and the NIH, including the Informatics Center for the NCI Early Detection Research Network (EDRN). For the EDRN, Mr. Crichton has developed a national infrastructure for the capture, management, distribution, and analysis of data from cancer biomarker research. He also architected an open source software framework, Apache OODT, for the management and distribution of massive scientific data. This won runner-up for NASA Software of the Year 2003, which is now hosted by the Apache Software Foundation as a top-level project, NASA’s first. Mr. Crichton recently served on the National Research Council Committee on the Analysis of Massive Data, which released its report on big data analytics in September 2013. He has published over 100 papers on software and information architectures, distributed systems, and scientific data management and analysis, as well as five book chapters.
Richard Doyle, Program Manager for Information and Data Science, Jet Propulsion Laboratory (JPL), California Institute of Technology
Richard J. Doyle is the Program Manager for Information and Data Science at the Jet Propulsion Laboratory in Pasadena, California. His research interests span data science, autonomous systems, computing systems, software engineering, space asset protection and related topics that apply computer science principles and capabilities to space missions. He is the NASA Project Manager for the High Performance Spaceflight Computing (HPSC) technology development effort jointly sponsored by NASA’s Space Technology Mission Directorate and the AFRL Space Vehicles Directorate. He has authored over fifty articles on machine learning, model-based reasoning, space-based computing, autonomous systems, and data science, as well as book chapters and magazine articles.
Dr. Doyle is an Associate Fellow of the American Institute of Aeronautics and Astronautics (AIAA) and a member of the AIAA Intelligent Systems Technical Committee. He holds the Ph.D. in Computer Science from the Massachusetts Institute of Technology where he was at the Artificial Intelligence Laboratory, one of the precursors to MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL). He is past Executive Council member of the Association for the Advancement of Artificial Intelligence (AAAI). He is a member of the Advisory Board for IEEE Intelligent Systems. He was General Chair for the International Symposium on Artificial Intelligence, Robotics and Automation in Space (i-SAIRAS), held in Los Angeles in 2007, and he was Local Arrangements Chair for the International Joint Conference on Artificial Intelligence (IJCAI-09) held in Pasadena in 2009.