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.



[CIG-2019][CIG-2018]

Latest News

October 2020: Ulugbek will talk at Quantitative Phase Imaging VII conference at SPIE Photonics West 2021 that will take place on 6-11 March 2021. We will talk about Scalable Image Reconstruction in Optical Tomography using Deep Priors.

October 2020: Ulugbek will talk at 2021 SIAM Conference on Computational Science and Engineering that will take place on 1-4 March 2021. We will present RARE: Image Reconstruction using Deep Priors Learned without Ground Truth in a session “Beyond the Classical Variational Regularization in Imaging: When Bayesian and Learning Methods Come to Rescue”.

October 2020: “Single-shot 3D holographic particle localization using deep priors trained on simulated data” was accepted to Computational Imaging Conference at IS&T Electronic Imaging 2021.

October 2020: New preprint Async-RED: A Provably Convergent Asynchronous Block Parallel Stochastic Method using Deep Denoising Priors.

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