Welcome to the Computational Imaging Group (CIG)!
Computational Imaging is a rapidly growing research area at the intersection of image processing, 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.
April 2022: Two abstracts accepted to 2022 Annual Meeting of American Association of Physicists in Medicine (AAPM) as Best-in-Physics award oral presentations.
April 2022: New preprint Plug-and-Play Methods for Integrating Physical and Learned Models in Computational Imaging.
March 2022: Deformation-Compensated Learning for Image Reconstruction without Ground Truth was accepted to IEEE Transactions on Medical Imaging.