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Organizing Committee
ESPCI ParisTech
University of Michigan
Colorado State University
Sandia National Laboratories
Schlumberger-Doll Research Center
University of California at Davis
Memorial University of Newfoundland
The MITRE Corporation (U.S. Naval Research Laboratory, ret.)
MIT
University of California at Irvine
University of Crete
Stanford University
Air Force Research Laboratory
Abstract
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.
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.
Synthetic aperture radar (SAR) image of Shenandoah National Park, Virginia, shaded relief colored by elevation, Shuttle Radar Topography Mission. Image credit: NASA/JPL.
Seismic image of thrust and fold structural geometry offshore Namibia. Image credit: Rob Butler, Virtual Seismic Atlas.
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Semester Schedule
Wednesday, September 06, 2017
9:00 AM - 4:00 PM EDT
Participant Check In
Location: 121 South Main Street, 11th Floor, Providence, RI, United States
3:30 - 4:00 PM EDT
Coffee/ Tea Break
Location: 11th Floor Collaborative Space
Thursday, September 07, 2017
2:00 - 3:00 PM EDT
Informal Introductions
3:00 - 4:00 PM EDT
Informal Afternoon Tea
Location: 11th Floor Collaborative Space
Friday, September 08, 2017
11:00 AM - 12:00 PM EDT
Grad Student/ Postdoc Meeting with the Director
Location: 11th Floor Conference Room
3:30 - 4:00 PM EDT
Coffee/ Tea Break
Location: 11th Floor Collaborative Space
Monday, September 11, 2017
8:00 - 8:20 AM EDT
Registration
Location: 121 South Main Street Providence RI 11th Floor Collaborative Space
8:20 - 8:30 AM EDT
Introduction
Location: 11th Floor Lecture Hall
9:45 - 10:30 AM EDT
Radar Intro Talk - Armin Doerry, Sandia National Laboratories
Location: 11th Floor Lecture Hall
10:30 - 10:45 AM EDT
Coffee/ Tea Break
Location: 11th Floor Collaborative Space
