World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
30
Citations
4005
World Ranking
14081
National Ranking
5585

Research.com Recognitions

  • 2016 - SIAM Fellow For contributions to the computational science of image reconstruction.

Overview

James G. Nagy is affiliated with Emory University in the United States and has contributed extensively to research in mathematics, computer science, and engineering. Their work spans multiple subfields including mathematical physics, computational mechanics, radiology, nuclear medicine and imaging, computational theory and mathematics, as well as computer vision and pattern recognition.

The scientist's research mainly focuses on numerical methods in inverse problems, sparse and compressive sensing techniques, matrix theory and algorithms, medical imaging techniques and applications, electromagnetic scattering and analysis, image and signal denoising methods, and advanced X-ray and CT imaging.

James G. Nagy has published papers in various well-known venues, including:

  • arXiv (Cornell University)
  • SIAM Journal on Scientific Computing
  • SIAM Journal on Matrix Analysis and Applications
  • Numerical Algorithms
  • SIAM Journal on Imaging Sciences

Recent papers authored or co-authored by James G. Nagy include:

  • Limited-Angle CT Reconstruction via the L1/L2 Minimization, 2021, SIAM Journal on Imaging Sciences
  • Minimizing L 1 over L 2 norms on the gradient, 2022, Inverse Problems
  • Iteratively Reweighted FGMRES and FLSQR for Sparse Reconstruction, 2021, SIAM Journal on Scientific Computing
  • Fast Deterministic Approximation of Symmetric Indefinite Kernel Matrices with High Dimensional Datasets, 2022, SIAM Journal on Matrix Analysis and Applications
  • An effective alternating direction method of multipliers for color image restoration, 2020, Applied Numerical Mathematics

Frequent co-authors collaborating with James G. Nagy are:

  • Malena Sabaté Landman
  • Ariana N. Brown
  • Julianne Chung
  • Min Tao
  • Yifei Lou

In recognition of their contributions to computational science, particularly in image reconstruction, James G. Nagy was named a SIAM Fellow in 2016.

Best Publications

  • Deblurring Images: Matrices, Spectra, and Filtering

    Per Christian Hansen;James G. Nagy;Dianne P. O'Leary

  • Restoring images degraded by spatially-variant blur

    James G. Nagy;Dianne P. O'Leary

  • Iterative Methods for Image Deblurring: A Matlab Object-Oriented Approach

    James G. Nagy;Katrina Palmer;Lisa Perrone

  • A weighted-GCV method for Lanczos-hybrid regularization.

    Julianne Chung;James G. Nagy;Dianne M. O'Leary

  • Preconditioned iterative regularization for Ill-posed problems

    Martin Hanke;James Nagy;Robert Plemmons

  • IR Tools: a MATLAB package of iterative regularization methods and large-scale test problems

    Silvia Gazzola;Per Christian Hansen;James G. Nagy

  • Enforcing nonnegativity in image reconstruction algorithms

    James G. Nagy;Zdenek Strakos

  • FFT-based preconditioners for Toeplitz-block least squares problems

    Raymond H. Chan;James G. Nagy;Robert J. Plemmons

  • Restoration of atmospherically blurred images by symmetric indefinite conjugate gradient techniques

    Martin Hanke;James G Nagy

  • Deblurring Images: Matrices, Spectra, and Filtering (Fundamentals of Algorithms 3) (Fundamentals of Algorithms)

    Per Christian Hansen;James G. Nagy;Dianne P. O'Leary

  • Iterative image restoration using approximate inverse preconditioning

    J.G. Nagy;R.J. Plemmons;T.C. Torgersen

  • KRONECKER PRODUCT AND SVD APPROXIMATIONS IN IMAGE RESTORATION

    Julie Kamm;James G. Nagy

  • Numerical methods for coupled super-resolution

    Julianne Chung;Eldad Haber;James Nagy

  • Quasi-Newton approach to nonnegative image restorations

    Martin Hanke;James G. Nagy;Curtis Vogel

  • Optimal Kronecker Product Approximation of Block Toeplitz Matrices

    Julie Kamm;James G. Nagy

  • Covariance-Preconditioned Iterative Methods for Nonnegatively Constrained Astronomical Imaging

    Johnathan M. Bardsley;James G. Nagy

  • Circulant Preconditioned Toeplitz Least Squares Iterations

    Raymond H. Chan;James G. Nagy;Robert J. Plemmons

  • Fast iterative image restoration with a spatially-varying PSF

    James G. Nagy;Dianne P. O'Leary

  • A computational method for the restoration of images with an unknown, spatially-varying blur

    Johnathan Bardsley;Stuart Jefferies;James Nagy;Robert Plemmons

  • Context aided video-to-text information fusion

    Erik Blasch;James G. Nagy;Alex Aved;Eric K. Jones

  • GENERALIZED ARNOLDI-TIKHONOV METHOD FOR SPARSE RECONSTRUCTION ∗

    Silvia Gazzola;James G. Nagy

  • An Efficient Iterative Approach for Large-Scale Separable Nonlinear Inverse Problems

    Julianne Chung;James G. Nagy

  • Kronecker Product Approximations for Image Restoration with Reflexive Boundary Conditions

    James G. Nagy;Michael K. Ng;Lisa Perrone

  • Steepest descent, CG, and iterative regularization of ill-posed problems

    J. G. Nagy;K. M. Palmer

Frequent Co-Authors

Robert J. Plemmons
Robert J. Plemmons Wake Forest University
Dianne P. O'Leary
Dianne P. O'Leary University of Maryland, College Park
Carlo Baccigalupi
Carlo Baccigalupi International School for Advanced Studies
Yifei Lou
Yifei Lou University of North Carolina at Chapel Hill
Raymond H. Chan
Raymond H. Chan Lingnan University
Eric L. Miller
Eric L. Miller Tufts University
Michael K. Ng
Michael K. Ng Hong Kong Baptist University
Gary G. Borisy
Gary G. Borisy ADA Forsyth Institute
Matteo Pastorino
Matteo Pastorino University of Genoa
Eldad Haber
Eldad Haber University of British Columbia

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