Welcome to the Computational Imaging Group (CIG)!

Computational Imaging is a rapidly growing research area at the intersection of image processing, computer vision, physical sciences, and machine learning. Computational Imaging Group (CIG) at Washington University researches new methods for reliable acquisition, efficient processing, and automated analysis of spatiotemporal data. Application include biomedical imaging, material sciences, geospatial intelligence, space exploration, industrial inspection, and consumer electronics. We develop algorithms and theoretical foundations for enabling advanced capabilities in future imaging systems. We have expertise in large-scale optimization, signal and image processing, machine learning, computer vision, and statistical inference. Our research is inherently interdisciplinary and includes collaborations with researchers in optics, medicine, physics, and biology.

To WashU students: If you want to explore research opportunities at CIG go to the list of available projects.


Latest News

June 2020: We are organizing a special issue on “Computational Microscopy” in Elsevier Optics Communications. Guest editors for the issue are H. B. de Aguiar (ENS, France), U. S. Kamilov (WashU, USA), and L. Tian (BU, USA).

May 2020: Our paper RARE: Image Reconstruction using Deep Priors Learned without Groundtruth was accepted to IEEE Journal of Selected Topics in Signal Processing.

May 2020: The journal version of our paper Block Coordinate Regularization by Denoising was accepted to IEEE Transactions on Computational Imaging.

May 2020: New manuscript Provable Convergence of Plug-and-Play Priors with MMSE denoisers.

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