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
October 2024: New paper Stochastic Deep Restoration Priors for Imaging Inverse Problems.
September 2024: Chicago Park has joined CIG as a PhD student. Chicago has previously done his BS in CS at WashU.
September 2024: New paper Gaussian is All You Need: A Unified Framework for Solving Inverse Problems via Diffusion Posterior Sampling.
September 2024: FLAIR: A Conditional Diffusion Framework with Applications to Face Video Restoration was accepted to WACV 2025.
August 2024: Bioengineering approaches for patient-specific analysis of placenta structure and function was accepted to Placenta.
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