Computational Imaging Group
Our mission
The Computational Imaging Group (CIG) at UW–Madison develops the mathematical and computational foundations of intelligent systems that sense, reconstruct, and understand the physical world. We study how to recover information from incomplete and noisy measurements by combining physical models, statistical inference, optimization, and generative AI. Our research connects fundamental theory with practical algorithms to advance imaging and sensing across science, medicine, and engineering.
Research
Computational Imaging
We develop mathematical models and algorithms that reconstruct images from incomplete, noisy, and indirect measurements, pushing the limits of what imaging systems can recover.
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Generative Modeling
We develop generative AI methods that learn complex signal and image distributions from data, and study how they enable efficient reconstruction, uncertainty quantification, and inference in high-dimensional inverse problems.
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Optimization and Inference
We advance the mathematical foundations of optimization and statistical inference for imaging and sensing, developing scalable, reliable algorithms that integrate physical models with learned representations.
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Imaging Applications
We work with scientists and clinicians to bring these methods to real imaging systems, including MRI, CT, PET and SPECT, optical microscopy, and seismic and remote sensing.
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Welcome to Harry Mellow, who has joined CIG as a PhD student.
Prof. Kamilov was a plenary speaker at IEEE ICIP 2026, which took place in Tampere, Finland.