World's Best Scientists 2026 revealed!

D-Index & Metrics

Mathematics

D-Index
32
Citations
4569
World Ranking
3179
National Ranking
1272

Moody T. Chu publication distribution in Mathematics in 2026

The chart shows the distribution of publications by all Research.com ranked scientists in the field of Mathematics in 2026. The highlighted bar marks where Moody T. Chu sits on this spectrum.

42–46 publications: 3 scientists 47–51 publications: 5 scientists 52–56 publications: 7 scientists 57–61 publications: 20 scientists 62–66 publications: 14 scientists 67–71 publications: 25 scientists 72–76 publications: 19 scientists 77–81 publications: 35 scientists 82–86 publications: 50 scientists 87–91 publications: 60 scientists 92–96 publications: 86 scientists 97–101 publications: 84 scientists 102–106 publications: 83 scientists 107–111 publications: 90 scientists 112–116 publications: 99 scientists 117–121 publications: 90 scientists 122–126 publications: 91 scientists 127–131 publications: 109 scientists 132–136 publications: 110 scientists 137–141 publications: 98 scientists 142–146 publications: 112 scientists 147–151 publications: 102 scientists 152–156 publications: 88 scientists 157–161 publications: 106 scientists 162–166 publications: 82 scientists 167–171 publications: 102 scientists 172–176 publications: 77 scientists 177–181 publications: 81 scientists 182–186 publications: 78 scientists 187–191 publications: 71 scientists 192–196 publications: 92 scientists 197–201 publications: 64 scientists 202–206 publications: 69 scientists 207–211 publications: 64 scientists 212–216 publications: 62 scientists 217–221 publications: 58 scientists 222–226 publications: 53 scientists 227–231 publications: 50 scientists 232–236 publications: 46 scientists 237–241 publications: 46 scientists 242–246 publications: 46 scientists 247–251 publications: 43 scientists 252–256 publications: 29 scientists 257–261 publications: 45 scientists 262–266 publications: 30 scientists 267–271 publications: 33 scientists 272–276 publications: 34 scientists 277–281 publications: 30 scientists 282–286 publications: 31 scientists 287–291 publications: 21 scientists 292–296 publications: 34 scientists 297–301 publications: 26 scientists 302–306 publications: 10 scientists 307–311 publications: 17 scientists 312–316 publications: 23 scientists 317–321 publications: 13 scientists 322–326 publications: 16 scientists 327–331 publications: 26 scientists 332–336 publications: 13 scientists 337–341 publications: 13 scientists 342–346 publications: 16 scientists 347–351 publications: 17 scientists 352–356 publications: 12 scientists 357–361 publications: 18 scientists 362–366 publications: 18 scientists 367–371 publications: 9 scientists 372–376 publications: 11 scientists 377–381 publications: 8 scientists 382–386 publications: 8 scientists 387–391 publications: 9 scientists 392–396 publications: 9 scientists 397–401 publications: 8 scientists 402–406 publications: 11 scientists 407–411 publications: 6 scientists 412–416 publications: 6 scientists 417–421 publications: 9 scientists 422–426 publications: 8 scientists 427–431 publications: 5 scientists 432–436 publications: 8 scientists 437–441 publications: 8 scientists 442–446 publications: 4 scientists 447–451 publications: 4 scientists 452–456 publications: 4 scientists 457–461 publications: 2 scientists 462–466 publications: 2 scientists 467–471 publications: 4 scientists 472–476 publications: 3 scientists 477–481 publications: 3 scientists 482–486 publications: 6 scientists 487–491 publications: 3 scientists 492–496 publications: 5 scientists 497–501 publications: 5 scientists 502–506 publications: 1 scientists 507–511 publications: 6 scientists 512–516 publications: 4 scientists 517–521 publications: 1 scientists 522–526 publications: 3 scientists 527–531 publications: 1 scientists 532–536 publications: 4 scientists 537+ publications: 100 scientists
42 publications 537+

This scientist: 110 publications — 16th percentile

16% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 537 publications or more.

Moody T. Chu D-index placement in Mathematics in 2026

The chart shows the D-index (discipline H-index) distribution of Mathematics scientists ranked by Research.com in 2026. The highlighted bar marks where Moody T. Chu sits on this spectrum.

30 D-Index: 174 scientists 31 D-Index: 151 scientists 32 D-Index: 174 scientists 33 D-Index: 117 scientists 34 D-Index: 136 scientists 35 D-Index: 127 scientists 36 D-Index: 145 scientists 37 D-Index: 153 scientists 38 D-Index: 150 scientists 39 D-Index: 150 scientists 40 D-Index: 137 scientists 41 D-Index: 136 scientists 42 D-Index: 93 scientists 43 D-Index: 108 scientists 44 D-Index: 115 scientists 45 D-Index: 112 scientists 46 D-Index: 103 scientists 47 D-Index: 75 scientists 48 D-Index: 59 scientists 49 D-Index: 67 scientists 50 D-Index: 60 scientists 51 D-Index: 57 scientists 52 D-Index: 59 scientists 53 D-Index: 62 scientists 54 D-Index: 60 scientists 55 D-Index: 50 scientists 56 D-Index: 42 scientists 57 D-Index: 54 scientists 58 D-Index: 50 scientists 59 D-Index: 42 scientists 60 D-Index: 41 scientists 61 D-Index: 35 scientists 62 D-Index: 40 scientists 63 D-Index: 21 scientists 64 D-Index: 31 scientists 65 D-Index: 27 scientists 66 D-Index: 29 scientists 67 D-Index: 19 scientists 68 D-Index: 25 scientists 69 D-Index: 17 scientists 70 D-Index: 18 scientists 71 D-Index: 12 scientists 72 D-Index: 14 scientists 73 D-Index: 13 scientists 74 D-Index: 18 scientists 75 D-Index: 9 scientists 76 D-Index: 11 scientists 77 D-Index: 10 scientists 78 D-Index: 9 scientists 79 D-Index: 16 scientists 80 D-Index: 12 scientists 81 D-Index: 10 scientists 82 D-Index: 5 scientists 83 D-Index: 5 scientists 84 D-Index: 13 scientists 85 D-Index: 6 scientists 86+ D-Index: 99 scientists
30 D-Index 86+

This scientist: 32 D-Index — 14th percentile

14% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 86 D-Index or more.

Overview

Moody T. Chu is affiliated with North Carolina State University in the United States and has contributed to research primarily in the fields of mathematics and computer science. Their scholarly work centers on computational mathematics, computational theory and mathematics, computational mechanics, artificial intelligence, as well as atomic and molecular physics and optics.

Their research addresses several main topics which include:

  • Tensor decomposition and applications
  • Matrix Theory and Algorithms
  • Quantum Information and Cryptography
  • Sparse and Compressive Sensing Techniques
  • Blind Source Separation Techniques
  • Elasticity and Material Modeling
  • Fluid Dynamics and Vibration Analysis

Among their frequent collaborators are Matthew M. Lin, Bo Dong, Nan Jiang, and Zhenyue Zhang.

Moody T. Chu has authored papers published in a variety of venues including SIAM Journal on Scientific Computing, Numerische Mathematik, IMA Journal of Numerical Analysis, Computer Physics Communications, and Quantum Information Processing.

Key publications by Moody T. Chu include:

  • Nonlinear Power-Like and SVD-Like Iterative Schemes with Applications to Entangled Bipartite Rank-1 Approximation, 2021, SIAM Journal on Scientific Computing
  • Lax dynamics for Cartan decomposition with applications to Hamiltonian simulation, 2023, IMA Journal of Numerical Analysis
  • A complex-valued gradient flow for the entangled bipartite low rank approximation, 2021, Computer Physics Communications

Other relevant works related to their coauthors, such as Bo Dong, include publications like "Nonlinear power-like iteration by polar decomposition and its application to tensor approximation" published in 2020 in Numerische Mathematik. Similarly, Matthew M. Lin has coauthored research in Quantum Information Processing on topics connected to multipartite quantum systems.

Best Publications

  • Inverse Eigenvalue Problems: Theory, Algorithms, and Applications

    Moody T. Chu;Gene H. Golub

  • Inverse Eigenvalue Problems

    Moody T. Chu

  • Structured inverse eigenvalue problems

    Moody T. Chu;Gene H. Golub

  • Structured low rank approximation

    Moody T. Chu;Robert E. Funderlic;Robert J. Plemmons

  • The projected gradient methods for least squares matrix approximations with spectral constraints

    Moody T. Chu;Kenneth R. Driessel

  • Optimality, computation, and interpretation of nonnegative matrix factorizations

    M. T. Chu;F. Diele;R. Plemmons;Stefania Ragni

  • A rank-one reduction formula and its applications to matrix factorizations

    Moody T. Chu;Robert E. Funderlic;Gene H. Golub

  • Parallel solution of ODE's by multi-block methods

    Moody T. Chu;Hans Hamilton

  • Linear algebra algorithms as dynamical systems

    Moody T. Chu

  • On the Continuous Realization of Iterative Processes

    Moody T. Chu

  • On a multivariate eigenvalue problem, part I: algebraic theory and a power method

    Moody T. Chu;J. Loren Watterson

  • The Generalized Toda Flow, the QR Algorithm and the Center Manifold Theory

    Moody T. Chu

  • Numerical methods for inverse singular value problems3

    Moody T. Chu

  • Spillover Phenomenon in Quadratic Model Updating

    Moody T. Chu;Biswa Datta;Wen-Wei Lin;Shufang Xu

  • On Inverse Quadratic Eigenvalue Problems with Partially Prescribed Eigenstructure

    Moody T. Chu;Yuen-Cheng Kuo;Wen-Wei Lin

  • Isospectral Flows and Abstract Matrix Factorizations

    Moody T. Chu;Larry K. Norris

  • Constructing symmetric nonnegative matrices with prescribed eigenvalues by differential equations

    Moody T. Chu;Kenneth R. Driessel

  • The Orthogonally Constrained Regression Revisited

    Moody T Chu;Nickolay T Trendafilov

  • A simple application of the homotopy method to symmetric eigenvalue problems

    Moody T. Chu

  • Updating quadratic models with no spillover effect on unmeasured spectral data

    Moody T. Chu;Wen-Wei Lin;Shu Fang Xu

  • A continuous Jacobi-like approach to the simultaneous reduction of real matrices

    Moody T. Chu

Frequent Co-Authors

Gene H. Golub
Gene H. Golub Stanford University
Robert J. Plemmons
Robert J. Plemmons Wake Forest University
Carl Tim Kelley
Carl Tim Kelley North Carolina State University
Raymond T. Ng
Raymond T. Ng University of British Columbia
Morteza G. Khaledi
Morteza G. Khaledi The University of Texas at Arlington
Liqun Qi
Liqun Qi Hong Kong Polytechnic University

If you think any of the details on this page are incorrect, let us know.

Report an issue

We appreciate your kind effort to assist us to improve this page, it would be helpful providing us with as much detail as possible in the text box below:

Related Online Degrees & Career Pathways

Mathematics graduates often explore related online degrees to enhance their career prospects. For those interested in business and leadership, pursuing one of the easiest mba programs can offer a flexible and accessible way to gain management skills without overwhelming coursework.

If you're looking to accelerate your education, some fastest online mba programs allow completion in a shorter timeframe, making it easier to enter the workforce or advance quickly in your field.

For professionals aiming to deepen expertise in finance, exploring cheap online masters in finance provides an affordable pathway to strengthen quantitative and financial analysis skills, leveraging a strong math background.

Additionally, business leaders or academics might consider a specialized degree like a 1 year dba program online to further their research and strategic management capabilities. These programs align well with analytical thinking and problem-solving skills honed in math studies.

Best Scientists Citing Moody T. Chu

Trending Scientists

Recently Published Articles