Abstract: Computational imaging aspires to bring together mathematics, physics, computer science, and applications to solve frontier problems in imaging. While it has made great progress and proved its potential, an enormous array of amazing new methods has gone unused in real applications. In particular, model-based iterative reconstruction (MBIR) is an example of a method with established value that is not widely used. In this talk, we take a hard look at why MBIR is not used and formulate a strategy to address these limitations in MBIRJAX, a software package that combines novel theoretical, software, and interface design to reduce barriers to entry for scientific, industrial, and commercial applications. ******Biography****** Charles A. Bouman is the Showalter Professor of Electrical and Computer Engineering and Biomedical Engineering at Purdue University. He received his B.S.E.E. degree from the University of Pennsylvania, M.S. degree from the University of California at Berkeley, and Ph.D. from Princeton University in 1989. He is a member of the National Academy of Inventors, a Fellow of the IEEE, AIMBE, and SPIE, and an Honorary Member of the IS&T. He is the recipient of the 2021 IEEE Signal Processing Society, Claude Shannon-Harry Nyquist Technical Achievement Award, the 2014 Electronic Imaging Scientist of the Year award, and the IS&T’s Raymond C. Bowman Award; and in 2020, his paper on Plug-and-Play Priors won the SIAM Imaging Science Best Paper Prize. He has served as the IEEE Signal Processing Society’s Vice President of Technical Directions, Editor-in-Chief of the IEEE Transactions on Image Processing, Vice President of Publications for the IS&T Society, and he led the creation of the IEEE