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 in CIG? Multiple opportunities at all levels.


[CIG-2021] [CIG-2019][CIG-2018]

Latest News

January 2022: Learning-based Motion Artifact Removal Networks (LEARN) for Quantitative R2* Mapping was accepted to Magnetic Resonance in Medicine.

January 2022: Yu Sun is invited to give a talk on “Integrating Physical Models and Learning Priors for Computational Imaging” at Stanford Computational Imaging Lab (SCI).

January 2022: Ulugbek will speak at the UG2+ workshop of CVPR 2022 on 19 June 2022.

January 2022: IEEE International Workshop on Computational Cameras and Displays (CCD) was accepted as a full-day workshop at CVPR 2022. This workshop is co-organized by Emma Alexander, Tali Dekel, He Sun, and Ulugbek Kamilov.

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