Charles A. Bouman

Charles A. Bouman is the Showalter Professor of Electrical and Computer Engineering and Biomedical Engineering at Purdue University, with a courtesy appointment in Mathematics. He is a leading researcher in computational imaging, integrating statistical signal processing, physics, and computation for applications in healthcare, scientific, and industrial imaging.

Education:

• B.S.E.E., University of Pennsylvania, 1981
• M.S., University of California at Berkeley, 1982
• Ph.D. in Electrical Engineering, Princeton University, 1989

His research focuses on computational imaging, including statistical image models, multiscale techniques, tomographic reconstruction, and fast algorithms. Key areas include Model-Based Iterative Reconstruction (MBIR), Plug-and-Play priors, document processing, and multiscale segmentation. His work has led to foundational contributions in total variation regularization and sparse-view reconstruction.

The recent publications highlight a strong trend in integrating machine learning with physical models for image reconstruction, particularly through Plug-and-Play methods. His work spans optical tomography, halftoning, image scaling, and document compression, demonstrating consistent innovation in both theory and practical software implementation.

Scientific Awards and Honors:

• Member, National Academy of Inventors
• Life Fellow, IEEE
• Fellow, IS&T; Honorary Member (2022); Service Award (2023)
• Fellow, SPIE and AIMBE
• IEEE Signal Processing Society Claude Shannon-Harry Nyquist Award (2021)
• Electronic Imaging Scientist of the Year (2014)
• SIAM Imaging Science Best Paper Prize (2020)
• Founder, IS&T Computational Imaging Conference (2003)
• Co-Founder, IEEE Transactions on Computational Imaging
• Vice President, IS&T; Former VP of Publications (2000–2004)

Bouman has advised numerous graduate students and leads a vibrant research group developing open-source tools like MBIRJAX, SVMBIR, and OpenMBIR. His research has been supported by the National Science Foundation, General Electric, Intel, Xerox, Hewlett-Packard, and the State of Indiana 21st Century Fund. He maintains an active presence through tutorials, conference leadership, and educational resources including video lectures and a textbook on Foundations of Computational Imaging.

Labs and Research Teams: His group develops cutting-edge software for tomographic reconstruction, clustering, segmentation, and dynamic sampling. Projects include Gaussian Mixture modeling (GMCluster), Plug-and-Play implementations, Sparse Matrix Transforms, and UAV sensing datasets. The research is highly interdisciplinary, bridging engineering, mathematics, and biomedical applications.