World's Best Scientists 2026 revealed!
J. Salvador Sánchez

J. Salvador Sánchez

D-Index & Metrics

Computer Science

D-Index
37
Citations
6240
World Ranking
10699
National Ranking
170

J. Salvador Sánchez publication distribution in Computer Science in 2026

The chart shows the distribution of publications by all Research.com ranked scientists in the field of Computer Science in 2026. The highlighted bar marks where J. Salvador Sánchez sits on this spectrum.

32–41 publications: 7 scientists 42–51 publications: 22 scientists 52–61 publications: 82 scientists 62–71 publications: 134 scientists 72–81 publications: 249 scientists 82–91 publications: 324 scientists 92–101 publications: 421 scientists 102–111 publications: 420 scientists 112–121 publications: 497 scientists 122–131 publications: 544 scientists 132–141 publications: 555 scientists 142–151 publications: 609 scientists 152–161 publications: 559 scientists 162–171 publications: 534 scientists 172–181 publications: 556 scientists 182–191 publications: 583 scientists 192–201 publications: 519 scientists 202–211 publications: 508 scientists 212–221 publications: 490 scientists 222–231 publications: 437 scientists 232–241 publications: 423 scientists 242–251 publications: 408 scientists 252–261 publications: 377 scientists 262–271 publications: 301 scientists 272–281 publications: 335 scientists 282–291 publications: 320 scientists 292–301 publications: 293 scientists 302–311 publications: 250 scientists 312–321 publications: 238 scientists 322–331 publications: 206 scientists 332–341 publications: 209 scientists 342–351 publications: 208 scientists 352–361 publications: 162 scientists 362–371 publications: 176 scientists 372–381 publications: 127 scientists 382–391 publications: 158 scientists 392–401 publications: 128 scientists 402–411 publications: 104 scientists 412–421 publications: 94 scientists 422–431 publications: 99 scientists 432–441 publications: 83 scientists 442–451 publications: 108 scientists 452–461 publications: 73 scientists 462–471 publications: 77 scientists 472–481 publications: 69 scientists 482–491 publications: 84 scientists 492–501 publications: 62 scientists 502–511 publications: 54 scientists 512–521 publications: 57 scientists 522–531 publications: 51 scientists 532–541 publications: 51 scientists 542–551 publications: 32 scientists 552–561 publications: 38 scientists 562–571 publications: 28 scientists 572–581 publications: 43 scientists 582–591 publications: 33 scientists 592–601 publications: 41 scientists 602–611 publications: 32 scientists 612–621 publications: 28 scientists 622–631 publications: 25 scientists 632–641 publications: 27 scientists 642–651 publications: 17 scientists 652–661 publications: 20 scientists 662–671 publications: 17 scientists 672–681 publications: 15 scientists 682–691 publications: 14 scientists 692–701 publications: 21 scientists 702–711 publications: 13 scientists 712–721 publications: 12 scientists 722–731 publications: 19 scientists 732–741 publications: 14 scientists 742–751 publications: 12 scientists 752–761 publications: 10 scientists 762–771 publications: 10 scientists 772–781 publications: 11 scientists 782–791 publications: 10 scientists 792–801 publications: 11 scientists 802–811 publications: 8 scientists 812–821 publications: 8 scientists 822–831 publications: 7 scientists 832–841 publications: 11 scientists 842–851 publications: 10 scientists 852–861 publications: 5 scientists 862–871 publications: 9 scientists 872–881 publications: 4 scientists 882–891 publications: 6 scientists 892–901 publications: 3 scientists 902–911 publications: 6 scientists 912–921 publications: 3 scientists 922–931 publications: 2 scientists 932–941 publications: 2 scientists 942–951 publications: 2 scientists 952–961 publications: 3 scientists 962–971 publications: 3 scientists 972–981 publications: 3 scientists 982–990 publications: 5 scientists 991+ publications: 100 scientists
32 publications 991+

This scientist: 143 publications — 24th percentile

24% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 991 publications or more.

J. Salvador Sánchez D-index placement in Computer Science in 2026

The chart shows the D-index (discipline H-index) distribution of Computer Science scientists ranked by Research.com in 2026. The highlighted bar marks where J. Salvador Sánchez sits on this spectrum.

30–31 D-Index: 879 scientists 32–33 D-Index: 983 scientists 34–35 D-Index: 918 scientists 36–37 D-Index: 990 scientists 38–39 D-Index: 968 scientists 40–41 D-Index: 907 scientists 42–43 D-Index: 821 scientists 44–45 D-Index: 763 scientists 46–47 D-Index: 689 scientists 48–49 D-Index: 543 scientists 50–51 D-Index: 543 scientists 52–53 D-Index: 518 scientists 54–55 D-Index: 500 scientists 56–57 D-Index: 458 scientists 58–59 D-Index: 400 scientists 60–61 D-Index: 337 scientists 62–63 D-Index: 308 scientists 64–65 D-Index: 292 scientists 66–67 D-Index: 249 scientists 68–69 D-Index: 213 scientists 70–71 D-Index: 192 scientists 72–73 D-Index: 189 scientists 74–75 D-Index: 165 scientists 76–77 D-Index: 139 scientists 78–79 D-Index: 119 scientists 80–81 D-Index: 121 scientists 82–83 D-Index: 113 scientists 84–85 D-Index: 88 scientists 86–87 D-Index: 87 scientists 88–89 D-Index: 75 scientists 90–91 D-Index: 69 scientists 92–93 D-Index: 57 scientists 94–95 D-Index: 46 scientists 96–97 D-Index: 38 scientists 98–99 D-Index: 34 scientists 100–101 D-Index: 36 scientists 102–103 D-Index: 27 scientists 104–105 D-Index: 37 scientists 106–107 D-Index: 18 scientists 108–109 D-Index: 31 scientists 110–111 D-Index: 19 scientists 112–113 D-Index: 16 scientists 114–115 D-Index: 12 scientists 116–117 D-Index: 20 scientists 118–119 D-Index: 15 scientists 120–121 D-Index: 5 scientists 122–123 D-Index: 20 scientists 124–125 D-Index: 8 scientists 126–127 D-Index: 5 scientists 128–129 D-Index: 7 scientists 130 D-Index: 3 scientists 131+ D-Index: 98 scientists
30 D-Index 131+

This scientist: 37 D-Index — 27th percentile

27% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 131 D-Index or more.

Overview

J. Salvador Sánchez is affiliated with Jaume I University in Spain and conducts research primarily in the fields of Computer Science and Decision Sciences. The scientist's research work spans several subfields, including Artificial Intelligence, Management Science and Operations Research, Electrical and Electronic Engineering, Computer Vision and Pattern Recognition, and Information Systems.

The researcher has focused extensively on topics related to imbalanced data classification techniques and stock market forecasting methods. Additional areas of investigation include forecasting techniques and applications, machine learning and data classification, electricity theft detection techniques, anomaly detection techniques and applications, and energy load and power forecasting.

Recent publications by J. Salvador Sánchez include the following papers:

  • DBIG-US: A two-stage under-sampling algorithm to face the class imbalance problem, 2020, Expert Systems with Applications
  • Ranking-based MCDM models in financial management applications: analysis and emerging challenges, 2020, Progress in Artificial Intelligence
  • A New Under-Sampling Method to Face Class Overlap and Imbalance, 2020, Applied Sciences
  • Deep transfer learning for the recognition of types of face masks as a core measure to prevent the transmission of COVID-19, 2022, Applied Soft Computing
  • Fuzzy-Based Time Series Forecasting and Modelling: A Bibliometric Analysis, 2022, Applied Sciences

J. Salvador Sánchez frequently publishes in several scientific venues. The primary publication platforms include Applied Sciences, SSRN Electronic Journal, IEEE Access, Expert Systems with Applications, and Progress in Artificial Intelligence.

The scientist has collaborated consistently with the following coauthors:

  • Vicente García
  • Angélica Guzmán-Ponce
  • Rosa María Valdovinos Rosas
  • Luís Palomero
  • J. Raymundo Marcial-Romero

Best Publications

  • Strategies for learning in class imbalance problems

    Unknown

  • The Imbalanced Training Sample Problem: Under or over Sampling?

    Ricardo Barandela;Rosa M. Valdovinos;J. Salvador Sánchez;Francesc J. Ferri

  • On the k-NN performance in a challenging scenario of imbalance and overlapping

    Unknown

  • Index of Balanced Accuracy: A Performance Measure for Skewed Class Distributions

    Unknown

  • Prototype selection for the nearest neighbour rule through proximity graphs

    J. S. Sánchez;F. Pla;F. J. Ferri

  • Analysis of new techniques to obtain quality training sets

    Unknown

  • On the suitability of resampling techniques for the class imbalance problem in credit scoring

    Unknown

  • On the use of neighbourhood-based non-parametric classifiers

    J. S. Sánchez;F. Pla;F. J. Ferri

  • Exploring the synergetic effects of sample types on the performance of ensembles for credit risk and corporate bankruptcy prediction

    Vicente García;Ana Isabel Marqués;J. Salvador Sánchez

  • Two-level classifier ensembles for credit risk assessment

    Unknown

  • An analysis of how training data complexity affects the nearest neighbor classifiers

    Unknown

  • An insight into the experimental design for credit risk and corporate bankruptcy prediction systems

    Vicente García;Ana I. Marqués;J. Salvador Sánchez

  • High training set size reduction by space partitioning and prototype abstraction

    Unknown

  • Experimental study on prototype optimisation algorithms for prototype-based classification in vector spaces

    M. Lozano;J. M. Sotoca;J. S. Sánchez;F. Pla

  • A very high level interface to teleoperate a robot via Web including augmented reality

    R. Marin;P.J. Sanz;J.S. Sanchez

  • Eliminating redundancy and irrelevance using a new MLP-based feature selection method

    Unknown

  • A stochastic approach to wilson's editing algorithm

    Fernando Vázquez;J. Salvador Sánchez;Filiberto Pla

  • Theoretical Analysis of a Performance Measure for Imbalanced Data

    V. Garcia;Ramon A. Mollineda;J. Salvador Sanchez

  • Data characterization for effective prototype selection

    Ramón A. Mollineda;J. Salvador Sánchez;José M. Sotoca

  • Nearest Neighbour Editing and Condensing Tools–Synergy Exploitation

    Unknown

  • DECISION BOUNDARY PRESERVING PROTOTYPE SELECTION FOR NEAREST NEIGHBOR CLASSIFICATION

    Ricardo Barandela;Francesc J. Ferri;J. Salvador Sánchez

  • Band Selection in Multispectral Images by Minimization of Dependent Information

    J.M. Sotoca;F. Pla;J.S. Sanchez

  • Using regression models for predicting the product quality in a tubing extrusion process

    Vicente García;J. Salvador Sánchez;Luis Alberto Rodríguez-Picón;Luis Carlos Méndez-González

  • Ranking-based MCDM models in financial management applications: analysis and emerging challenges

    Ana I. Marqués;Vicente García;J. Salvador Sánchez

  • Mapping microarray gene expression data into dissimilarity spaces for tumor classification

    Vicente García;J. Salvador Sánchez

  • Online reconstruction-free single-pixel image classification

    Pedro Latorre-Carmona;V. Javier Traver;J. Salvador Sánchez;Enrique Tajahuerce

  • Cluster validation using information stability measures

    Damaris Pascual;Filiberto Pla;J. Salvador Sánchez

  • Nearest Neighbour Classifiers for Streaming Data with Delayed Labelling

    L.I. Kuncheva;J.S. Sanchez

  • Improving the k -NCN classification rule through heuristic modifications

    J. S. Sánchez;F. Pla;F. J. Ferri

  • Dynamic and static weighting in classifier fusion

    Rosa M. Valdovinos;J. Salvador Sánchez;Ricardo Barandela

  • An integral automation of industrial fruit and vegetable sorting by machine vision

    F. Pla;J.M. Sanchiz;J.S. Sanchez

  • A bias correction function for classification performance assessment in two-class imbalanced problems

    Vicente García;Ramón A. Mollineda;J. Salvador Sánchez

Frequent Co-Authors

Filiberto Pla
Filiberto Pla Jaume I University

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