Bio: John is a Senior Computer Scientist in the Office of Computational and Information Science and Technology (CISTO). His work focuses on the development of new information technologies, with with a particular emphasis on biodiversity and the environment. John's scientific and technical expertise is in bioinformatics, avian ecology, ecosystem modeling, the human/computer interface, and computing environments of the future. Over the past twenty-five years, he has taught, lead research teams, conducted basic and applied research, and advised on issues related to these areas of interest.
Most recently, John has lead the Applied Sciences Program's Invasive Species Forecasting System (ISFS) project. He is a Fellow of the American Association for the Advancement of Science (AAAS), a former member of the Biodiversity and Ecosystems Panel of the President's Committee of Advisors on Science and Technology (PCAST), and a current Commissioner of the Accreditation Board for Engineering and Technology (ABET). When not writing proposals, he's likely to be rehabing a house, swimming, or diving.

In general, the Environment distributes data communication tasks among the sensors and other elements (viewed as peers, each assigned a peer- role) and controls the flow of data. This work encompasses dynamic discovery, monitoring, control, and configuration as well as autonomous operations, real-time modeling and data processing, and secure ubiquitous communications. Specifically, the recent work focuses on integrating remote geomagnetic sensors, each having operating modes to manage, with modeling processes (also with remotely managed modes). We achieved a simple form of system autonomy through a feedback loop which uses model output to drive the remote management of system elements. In addition, we have implemented basic identity management features; providing mechanisms which restrict data-serving privileges to authorized users, and which allow improved trust and accountability among users of the Environment. Browsing peers access trusted near-real-time global, and on-demand regional, representations of geomagnetic activity "nowcasted" from dynamic sensor-reported values, but also have the option to access trusted sensors directly.

Bio: Matt Holland received his Bachelor of Science in Electrical Engineering from the University of Maryland at College Park in 2001; completing a curriculum focused on computer science, signal processing and communication systems. Originally hired while still in his senior year, his work at Goddard (mostly in Code 587 of AETD's Software Engineering Division) has been split between science data processing support of space weather and geospace missions, while collocated with the science teams, and in-house technology R&D efforts to improve Goddard's science data processing capabilities.

Imaging terrestrial planets, that are typically 10-10 times dimmer in visible light than the parent star and embedded in a sea of dust comprising the exo-zodiacal disk, represents a very difficult imaging problem. Any technique requires coronagraphic suppression of the starlight to increase the contrast of the planet with respect to residual diffraction and scattered light. NASA is assessing a multitude of such techniques via simulation and by a series of laboratory testbed. Herein will be discussed the general exoplanet detection and characterization problem and an assessment of the most promising techniques and their status.

Bio: Richard Lyon is an optical scientist in NASA Goddard Space Flight Center's Exoplanets and Stellar Astrophysics Lab. He is developing techniques for the direct detection of exoplanets, imaging interferometry and wavefront sensing and control. R. Lyon is the project scientist for the proposed Exosolar Planetary Imaging Coronagraph (EPIC) mission and has in the past been involved with the Hubble Space Telescope and the James Webb Space Telescope as well as numerous laboratory testbed efforts. He holds multiple awards and NASA's Medal for Exceptional Achievement and has approximately 135 publications in astrophysics, optics and applied mathematics.