Prof. Karl’s current research interests cover the following areas:

  • Computational Imaging
  • Multidimensional statistical signal and image processing
  • Detection and estimation, high-dimensional inference
  • Inverse problems, tomography
  • Geometric estimation
  • Biological and medical signal and image processing

Prof. Karl is interested in the general areas of multidimensional and multiresolution signal and image processing and estimation and geometric-based estimation. The projects that motivate this research include, but are not limited to, problems arising in automatic target detection and recognition (synthetic aperture radar), geophysical inverse problems (such as finding oil and analyzing the atmosphere), and medical estimation problems (such as tomography and MRI). The general goal is to develop efficient methods for the extraction of information from diverse data sources in the presence of uncertainty. The approach taken is based on the development of statistical models for both observations and prior knowledge and the subsequent use of these models for optimal or near-optimal processing.