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Mauricio D. Sacchi

Mauricio D. Sacchi

D-Index & Metrics

Engineering and Technology

D-Index
58
Citations
13721
World Ranking
2468
National Ranking
101

Mauricio D. Sacchi publication distribution in Engineering and Technology in 2026

The chart shows the distribution of publications by all Research.com ranked scientists in the field of Engineering and Technology in 2026. The highlighted bar marks where Mauricio D. Sacchi sits on this spectrum.

38–47 publications: 20 scientists 48–57 publications: 35 scientists 58–67 publications: 96 scientists 68–77 publications: 135 scientists 78–87 publications: 190 scientists 88–97 publications: 259 scientists 98–107 publications: 283 scientists 108–117 publications: 369 scientists 118–127 publications: 341 scientists 128–137 publications: 386 scientists 138–147 publications: 372 scientists 148–157 publications: 457 scientists 158–167 publications: 415 scientists 168–177 publications: 407 scientists 178–187 publications: 421 scientists 188–197 publications: 378 scientists 198–207 publications: 403 scientists 208–217 publications: 317 scientists 218–227 publications: 346 scientists 228–237 publications: 321 scientists 238–247 publications: 260 scientists 248–257 publications: 280 scientists 258–267 publications: 240 scientists 268–277 publications: 214 scientists 278–287 publications: 242 scientists 288–297 publications: 203 scientists 298–307 publications: 166 scientists 308–317 publications: 154 scientists 318–327 publications: 175 scientists 328–337 publications: 159 scientists 338–347 publications: 99 scientists 348–357 publications: 131 scientists 358–367 publications: 106 scientists 368–377 publications: 118 scientists 378–387 publications: 97 scientists 388–397 publications: 108 scientists 398–407 publications: 82 scientists 408–417 publications: 71 scientists 418–427 publications: 64 scientists 428–437 publications: 55 scientists 438–447 publications: 54 scientists 448–457 publications: 60 scientists 458–467 publications: 47 scientists 468–477 publications: 40 scientists 478–487 publications: 30 scientists 488–497 publications: 29 scientists 498–507 publications: 38 scientists 508–517 publications: 40 scientists 518–527 publications: 32 scientists 528–537 publications: 23 scientists 538–547 publications: 28 scientists 548–557 publications: 23 scientists 558–567 publications: 19 scientists 568–577 publications: 16 scientists 578–587 publications: 17 scientists 588–597 publications: 18 scientists 598–607 publications: 22 scientists 608–617 publications: 15 scientists 618–627 publications: 9 scientists 628–637 publications: 11 scientists 638–647 publications: 21 scientists 648–657 publications: 12 scientists 658–667 publications: 9 scientists 668–677 publications: 11 scientists 678–687 publications: 9 scientists 688–697 publications: 6 scientists 698–707 publications: 14 scientists 708–717 publications: 7 scientists 718–727 publications: 8 scientists 728–737 publications: 10 scientists 738–747 publications: 9 scientists 748–757 publications: 5 scientists 758–767 publications: 5 scientists 768–777 publications: 11 scientists 778–787 publications: 7 scientists 788–797 publications: 2 scientists 798–803 publications: 4 scientists 804+ publications: 100 scientists
38 publications 804+

This scientist: 406 publications — 90th percentile

90% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 804 publications or more.

Mauricio D. Sacchi D-index placement in Engineering and Technology in 2026

The chart shows the D-index (discipline H-index) distribution of Engineering and Technology scientists ranked by Research.com in 2026. The highlighted bar marks where Mauricio D. Sacchi sits on this spectrum.

30 D-Index: 59 scientists 31 D-Index: 114 scientists 32 D-Index: 129 scientists 33 D-Index: 189 scientists 34 D-Index: 200 scientists 35 D-Index: 262 scientists 36 D-Index: 311 scientists 37 D-Index: 312 scientists 38 D-Index: 350 scientists 39 D-Index: 385 scientists 40 D-Index: 348 scientists 41 D-Index: 362 scientists 42 D-Index: 426 scientists 43 D-Index: 380 scientists 44 D-Index: 310 scientists 45 D-Index: 341 scientists 46 D-Index: 301 scientists 47 D-Index: 306 scientists 48 D-Index: 271 scientists 49 D-Index: 246 scientists 50 D-Index: 210 scientists 51 D-Index: 253 scientists 52 D-Index: 213 scientists 53 D-Index: 221 scientists 54 D-Index: 195 scientists 55 D-Index: 186 scientists 56 D-Index: 170 scientists 57 D-Index: 167 scientists 58 D-Index: 166 scientists 59 D-Index: 144 scientists 60 D-Index: 152 scientists 61 D-Index: 141 scientists 62 D-Index: 138 scientists 63 D-Index: 131 scientists 64 D-Index: 118 scientists 65 D-Index: 114 scientists 66 D-Index: 119 scientists 67 D-Index: 95 scientists 68 D-Index: 87 scientists 69 D-Index: 77 scientists 70 D-Index: 89 scientists 71 D-Index: 69 scientists 72 D-Index: 54 scientists 73 D-Index: 46 scientists 74 D-Index: 55 scientists 75 D-Index: 54 scientists 76 D-Index: 49 scientists 77 D-Index: 53 scientists 78 D-Index: 46 scientists 79 D-Index: 28 scientists 80 D-Index: 39 scientists 81 D-Index: 36 scientists 82 D-Index: 24 scientists 83 D-Index: 26 scientists 84 D-Index: 36 scientists 85 D-Index: 18 scientists 86 D-Index: 25 scientists 87 D-Index: 19 scientists 88 D-Index: 26 scientists 89 D-Index: 27 scientists 90 D-Index: 23 scientists 91 D-Index: 15 scientists 92 D-Index: 12 scientists 93 D-Index: 9 scientists 94 D-Index: 15 scientists 95 D-Index: 10 scientists 96 D-Index: 13 scientists 97 D-Index: 13 scientists 98 D-Index: 9 scientists 99 D-Index: 7 scientists 100 D-Index: 7 scientists 101 D-Index: 8 scientists 102 D-Index: 7 scientists 103 D-Index: 7 scientists 104 D-Index: 9 scientists 105 D-Index: 6 scientists 106 D-Index: 9 scientists 107+ D-Index: 99 scientists
30 D-Index 107+

This scientist: 58 D-Index — 75th percentile

75% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 107 D-Index or more.

Overview

Mauricio D. Sacchi is affiliated with the University of Alberta in Canada and has contributed extensively to research in Earth and Planetary Sciences as well as Engineering. Their academic output places a strong focus on Geophysics, with a significant number of publications also intersecting subfields such as Ocean Engineering, Computer Vision and Pattern Recognition, Artificial Intelligence, and Mechanical Engineering.

The primary topics in their research include seismic imaging and inversion techniques, seismic waves and analysis, and geophysical methods and applications. Additional focus areas cover image and signal denoising methods, reservoir engineering and simulation methods, seismology and earthquake studies, and ultrasonics and acoustic wave propagation.

Key recent papers authored or co-authored by Mauricio D. Sacchi include:

  • "Efficient Tensor Completion Methods for 5-D Seismic Data Reconstruction: Low-Rank Tensor Train and Tensor Ring", 2022, IEEE Transactions on Geoscience and Remote Sensing
  • "Separation of simultaneous sources acquired with a high blending factor via coherence pass robust Radon operators", 2020, Geophysics
  • "Interpolated multichannel singular spectrum analysis: A reconstruction method that honors true trace coordinates", 2020, Geophysics
  • "Accelerating seismic scattered noise attenuation in offset-vector tile domain: Application of deep learning", 2022, Geophysics
  • "Least-squares reverse time migration via deep learning-based updating operators", 2022, Geophysics

Their frequent co-authors include Dawei Liu, Rongzhi Lin, Xiaokai Wang, Wenchao Chen, and Yi Guo. Collaboration with these researchers reflects a network of work primarily within the fields of seismic data processing and geophysical signal analysis.

Mauricio D. Sacchi has published in a range of specialized venues, with the most publications appearing in the journal Geophysics, followed by IEEE Transactions on Geoscience and Remote Sensing. Other notable publication venues include the Second International Meeting for Applied Geoscience & Energy, Geophysical Journal International, and the Journal of Applied Geophysics.

Best Publications

  • Simultaneous seismic data denoising and reconstruction via multichannel singular spectrum analysis

    Vicente Oropeza;Mauricio Sacchi

  • High‐resolution velocity gathers and offset space reconstruction

    Mauricio D. Sacchi;Tadeusz J. Ulrych

  • Latest views of the sparse Radon transform

    Daniel Trad;Tadeusz Ulrych;Mauricio Sacchi

  • Minimum weighted norm interpolation of seismic records

    Bin Liu;Mauricio D. Sacchi

  • Interpolation and extrapolation using a high-resolution discrete Fourier transform

    M.D. Sacchi;T.J. Ulrych;C.J. Walker

  • Accurate interpolation with high-resolution time-variant Radon transforms

    Daniel O. Trad;Tadeusz J. Ulrych;Mauricio D. Sacchi

  • Simulated annealing inversion of multimode Rayleigh wave dispersion curves for geological structure

    K. S. Beaty;D. R. Schmitt;M. Sacchi

  • A Bayes tour of inversion: A tutorial

    Tadeusz J. Ulrych;Mauricio D. Sacchi;Alan Woodbury

  • High-resolution three-term AVO inversion by means of a Trivariate Cauchy probability distribution

    Wubshet Alemie;Mauricio D. Sacchi

  • Least‐squares wave‐equation migration for AVP/AVA inversion

    Henning Kühl;Mauricio D. Sacchi

  • Reweighting strategies in seismic deconvolution

    Mauricio D. Sacchi

  • Beyond alias hierarchical scale curvelet interpolation of regularly and irregularly sampled seismic data

    Mostafa Naghizadeh;Mauricio D. Sacchi

  • Fourier reconstruction of nonuniformly sampled, aliased seismic data

    P. M. Zwartjes;M. D. Sacchi

  • A tensor higher-order singular value decomposition for prestack seismic data noise reduction and interpolation

    Nadia Kreimer;Mauricio D. Sacchi

  • Denoising seismic data using the nonlocal means algorithm

    David Bonar;Mauricio Sacchi

  • Multistep autoregressive reconstruction of seismic records

    Mostafa Naghizadeh;Mauricio D. Sacchi

  • Simultaneous source separation using a robust Radon transform

    Amr Ibrahim;Mauricio D. Sacchi

  • Tensor completion based on nuclear norm minimization for 5D seismic data reconstruction

    Nadia Kreimer;Aaron Stanton;Mauricio D. Sacchi

  • A fast reduced-rank interpolation method for prestack seismic volumes that depend on four spatial dimensions

    Jianjun Gao;Mauricio D. Sacchi;Xiaohong Chen

  • Interpolation and denoising of high-dimensional seismic data by learning a tight frame

    Siwei Yu;Jianwei Ma;Xiaoqun Zhang;Mauricio D. Sacchi

  • A Fast and Automatic Sparse Deconvolution in the Presence of Outliers

    A. Gholami;M. D. Sacchi

Frequent Co-Authors

Douglas R. Schmitt
Douglas R. Schmitt Purdue University West Lafayette
Sergey Fomel
Sergey Fomel The University of Texas at Austin
Jianwei Ma
Jianwei Ma Harbin Institute of Technology
Mirko van der Baan
Mirko van der Baan University of Alberta
Michael G. Bostock
Michael G. Bostock University of British Columbia
Jeroen Ritsema
Jeroen Ritsema University of Michigan–Ann Arbor

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