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.

Interested in doing research with us? Multiple opportunities at all levels.



[CIG-2019][CIG-2018]

Latest News

June 2021: New manuscript Recovery Analysis for Plug-and-Play Priors using the Restricted Eigenvalue Condition.

June 2021: CIG will be presenting three papers at IEEE International Conference on Image Processing (ICIP) this year.

June 2021: Ulugbek will give a talk at the Mathematics, Physics & Machine Learning seminar series on Friday, 11 June 2021. Form more info read here.

May 2021: SGD-Net: Efficient Model-Based Deep Learning with Theoretical Guarantees was accepted to IEEE Transactions on Computational Imaging.

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