Welcome to CIG!
Computational Imaging is a rapidly growing research area at the intersection of artificial intelligence, computer vision, image processing, applied mathematics, and physical sciences. Computational Imaging Group (CIG) advances 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.
Latest News
December 2024: New paper Random Walks with Tweedie: A Unified Framework for Diffusion Models.
December 2024: New paper FiRe: Fixed-points of Restoration Priors for Solving Inverse Problems.
November 2024: New paper ADOBI: Adaptive Diffusion Bridge For Blind Inverse Problems with Application to MRI Reconstruction.
November 2024: Fast motion-compensated reconstruction for 4D-CBCT using deep learning-based groupwise registration was accepted to Biomedical Physics & Engineering Express.
October 2024: New paper Stochastic Deep Restoration Priors for Imaging Inverse Problems.
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