ICERM Semester Program on "Mathematical and Computational Challenges in Radar and Seismic Reconstruction"
(September 6 - December 8, 2017)

Synthetic aperture radar (SAR) image of Shenandoah National Park, Virginia, shaded relief colored by elevation, Shuttle Radar Topography Mission. Image credit: NASA/JPL.


Inversion and imaging with waves is of fundamental importance in both radar and seismic reconstruction. Mathematics provides the key technology in both areas and, despite differing in many important respects, they have much in common in their underlying mathematical frameworks, approaches, and challenges. This semester program will focus on advancing their common mathematical and computational methodologies, as well as selected subjects distinct to each area, in the context of new challenges and opportunities that have arisen in recent years. Both theory and applications will be of interest. Participants will be drawn from academia, industry, and governmental laboratories in order to broadly address theory, applications, and their synergy.

The program will be influenced by recent developments in wave propagation and imaging, data acquisition and analysis, and high-performance computing. Driven by the ongoing need for more realistic mathematical models and simulations, recent advances in wave propagation and imaging in complex media are increasingly convincing and competitive but present new challenges. New sensor technologies have led to new types of data that can be collected, as well as to unprecedented volumes of data. This wealth of data offers new potential for gaining insights but also poses new needs for large-scale data-analysis algorithms that can effectively exploit advances in computing.

There is an outstanding opportunity to build on these developments and to bring the field to new levels of realistic inversion scenarios and problem scales. Topics to be considered in the semester program include wave propagation, inversion, and imaging in random media; statistical aspects of inverse problems, including homogenization and uncertainty quantification; optimization methods for inversion and imaging; large-scale computation and inverse problems, including methods for model reduction and large-scale optimization; and subjects of particular interest in radar reconstruction or in seismic inversion.

Seismic image of thrust and fold structural geometry offshore Namibia. Image credit: Rob Butler, Virtual Seismic Atlas.

Semester Program and Research Cluster Organizers

Associated Events & Information

Fall 2017 Semester Workshops

September 11 - 13, 2017Industrial Problems in Radar and Seismic Reconstruction Liliana Borcea, Margaret Cheney, Armin Doerry, Vladimir Druskin, Frank Robey. Burt Tilley, Suzanne Weekes
September 25 - 29, 2017Waves and Imaging in Random Media Josselin Garnier, Kui Ren, Chrysoula Tsogka
October 16 - 20, 2017Mathematical and Computational Aspects of Radar Imaging Margaret Cheney, Armin Doerry, Eric Mokole, Frank Robey
November 6 - 10, 2017Recent Advances in Seismic Modeling and Inversion: From Analysis to Applications Maarten de Hoop, Vladimir Druskin, Alison Malcolm, Alexander Mamonov, Lexing Ying

Fall 2017 Research Clusters

September 6 - October 13, 2017)Research Cluster 1: Wave Propagation and Imaging in Random Media Alexandre Aubry, Liliana Borcea, Albert Fannjiang, Knut Solna, Chrysoula Tsogka
October 2 - November 3, 2017Research Cluster 2: Mathematical and Computational Aspects of Radar Imaging Margaret Cheney, Armin Doerry, Eric Mokole, Frank Robey, Ed Zelnio
October 23 - November 21, 2017Research Cluster 3: Wave Propagation and Inversion in Seismic Applications Vladimir Druskin, Alison Malcolm, Lexing Ying

This page will show upcoming seminars that will be scheduled by organizers, speakers, and participants of the Fall 2017 semester program. Walk-ins are welcomed and encouraged for these seminars. Please check back regularly for updates.

We provide an iCal link for those attendees who wish to sync their own devices and/or calendars to our schedule.

= speaker   = poster presenter