Mathematics in Imaging (MATH) covers two fundamental aspects of imaging: the physical and mathematical modeling of imaging process and the design and analysis of novel theory and algorithms to address the important challenges related to image reconstruction.

This meeting is an opportunity to gather people from optics, mathematics, and signal processing to cross-fertilize these fields with discussions on novel technologies, methodologies and challenges.
Communications that are not directly related to imaging, but could be of interest to the field or unsolved challenges in optics, requiring advanced signal processing tools are particularly welcome.

Committee Members

  • Lei Tian, Boston University, United States , Chair
  • P. Scott Carney, University of Rochester, United States , Program Chair
  • Pierre Weiss, Université de Toulouse, CNRS, France , Program Chair
  • Ayman Abouraddy, University of Central Florida, CREOL, United States
  • Miguel Alonso, University of Rochester, France
  • Alexandre Aubry, Institut Langevin, France
  • Stanley Chan, Purdue University, United States
  • Wonshik Choi, Korea University, South Korea
  • James Fienup, University of Rochester, United States
  • Ulugbek Kamilov, Washington University in St. Louis, United States
  • Clem Karl, Boston University, United States
  • Anne Sentenac, Fresnel Institut, France
  • Gabriele Steidl, Technische Universität Kaiserslautern, Germany
  • Tanja Tarvainen, University of Eastern Finland, Finland
  • Markus Testorf, Dartmouth College, United States


Lei Tian

Boston University, UNITED STATES

P. Scott Carney

University of Rochester, UNITED STATES
Program Chair

Pierre Weiss

Université de Toulouse, CNRS, FRANCE
Program Chair