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

Latest News

December 2021: New preprint Zero-Shot Learning of Continuous 3D Refractive Index Maps from Discrete Intensity-Only Measurements.

December 2021: Ulugbek gives a seminar at the Computational Imaging Seminar Series of Purdue University on Wednesday, 1 December 2021.

October 2021: CoIL: Coordinate-based Internal Learning for Tomographic Imaging was accepted to IEEE Transactions on Computational Imaging.

October 2021: Yuyang Hu and Flora Sun are recipients of the Dean’s Select PhD Fellowship from the Washington University McKelvey School of Engineering. Congratulations with this achievement!

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