Stochastic inverse problems arise when a blurred version of a desired signal or image influences the statistics of a random process that models measured data. Examples include the quantum- limited imaging of radioactive tracers in the body, imaging gamma-ray sources in astronomy, and forming images in low-light photography. A joint group research program is being pursued with Alan Karr at the Johns Hopkins University to investigate new algorithms for these problems. Identifying algorithms which map onto highly parallel computational architectures is an important objective of the research.
