Welcome to CIG!

Computational Imaging is a rapidly growing research area at the intersection of data science, computer vision, machine learning, applied mathematics, and physical sciences. Computational Imaging Group (CIG) develops advanced algorithms for fast and reliable acquisition, efficient processing, and automated analysis of imaging data, including 2D, 3D, or 4D images and videos. Applications include biomedical imaging, material sciences, geospatial sensing, space exploration, industrial inspection, and consumer electronics. We develop algorithms and theoretical foundations for enabling advanced capabilities in future imaging and sensing systems. We have expertise in deep learning, large-scale optimization, signal and image processing, computer vision, and statistical inference. Our research is inherently interdisciplinary and includes collaborations with researchers in optics, medicine, physics, materials, and biology.

Interested in doing research in CIG? Multiple opportunities at all levels.


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Latest News

December 2022: Ulugbek will give an invited talk at EPFL on Computational Imaging: Integrating Physical and Learned Models on 19 December 2022.

December 2022: Ulugbek will give an invited talk at Institut de Mathématiques de Bordeaux on Plug-and-Play Models for Large-Scale Computational Imaging on 15 December 2022.

December 2022: Ulugbek will give an invited talk at ENS de Lyon on Plug-and-Play Models for Large-Scale Computational Imaging on 9 December 2022. The slides are available here.

December 2022: Deep-Learning-Based Accelerated and Noise-Suppressed Estimation (DANSE) of quantitative Gradient Recalled Echo (qGRE) MRI metrics associated with Human Brain Neuronal Structure and Hemodynamic Properties was accepted to NMR in Biomedicine.

December 2022: Deep learning-based motion compensation for four-dimensional cone-beam computed tomography (4D-CBCT) reconstruction was accepted to Medical Physics.

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