World's Best Scientists 2026 revealed!
Joaquín Abellán

Joaquín Abellán

D-Index & Metrics

Computer Science

D-Index
31
Citations
3056
World Ranking
13775
National Ranking
270

Joaquín Abellán 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 Joaquín Abellán 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: 87 publications — 5th percentile

5% of scientists in this discipline score the same or lower.

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

Joaquín Abellán 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 Joaquín Abellán 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: 31 D-Index — 6th percentile

6% of scientists in this discipline score the same or lower.

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

Overview

Joaquín Abellán is affiliated with the University of Granada in Spain. Their research primarily focuses on the field of computer science, with a notable concentration in artificial intelligence. Additional subfields of study include management science and operations research, computational theory and mathematics, information systems, and statistics and probability.

Their work addresses various specialized topics such as Bayesian modeling and causal inference, multi-criteria decision making, rough sets and fuzzy logic, imbalanced data classification techniques, data mining algorithms and applications, text and document classification technologies, and machine learning and data classification.

Joaquín Abellán has contributed to several scientific papers including:

  • Combination in the theory of evidence via a new measurement of the conflict between evidences (2021, Expert Systems with Applications)
  • Critique of modified Deng entropies under the evidence theory (2020, Chaos Solitons & Fractals)
  • Using Credal C4.5 for Calibrated Label Ranking in Multi-Label Classification (2022, International Journal of Approximate Reasoning)
  • Required mathematical properties and behaviors of uncertainty measures on belief intervals (2021, International Journal of Intelligent Systems)
  • Maximum of Entropy for Belief Intervals Under Evidence Theory (2020, IEEE Access)

Frequent coauthors collaborating with Joaquín Abellán include Serafín Moral-García, Carlos J. Mantas, Javier G. Castellano, María D. Benítez, and Tahani Coolen-Maturi.

The scientist's research outputs have been published often in venues such as Expert Systems with Applications, International Journal of Approximate Reasoning, IEEE Access, Applied Soft Computing, and Entropy.

Best Publications

  • Analysis of traffic accident severity using Decision Rules via Decision Trees

    JoaquíN AbelláN;Griselda LóPez;Juan De OñA

  • A comparative study on base classifiers in ensemble methods for credit scoring

    Joaquín Abellán;Javier G. Castellano

  • Improving experimental studies about ensembles of classifiers for bankruptcy prediction and credit scoring

    Joaquín Abellán;Carlos J. Mantas

  • Credal-C4.5: Decision tree based on imprecise probabilities to classify noisy data

    Carlos Javier Mantas;Joaquín Abellán

  • Building Classification Trees Using the Total Uncertainty Criterion

    Joaquín Abellán;Serafín Moral

  • Extracting decision rules from police accident reports through decision trees

    Juan de Oña;Griselda López;Joaquín Abellán

  • A comparison of random forest based algorithms: random credal random forest versus oblique random forest

    Carlos Javier Mantas;Javier G. Castellano;Serafín Moral-García;Joaquín Abellán

  • Requirements for total uncertainty measures in Dempster–Shafer theory of evidence

    Joaquín Abellán;Andrés R. Masegosa

  • Analyzing properties of Deng entropy in the theory of evidence

    Joaquín Abellán

  • Maximum of entropy for credal sets

    Joaquin Abellan;Serafin Moral

  • Upper entropy of credal sets. Applications to credal classification

    Joaquín Abellán;Serafín Moral

  • A Random Forest approach using imprecise probabilities

    Joaquín Abellán;Carlos Javier Mantas;Javier G. Castellano

  • A non-specificity measure for convex sets of probability distributions

    Joaquin Abellan;Serafin Moral

  • Bagging schemes on the presence of class noise in classification

    Joaquín Abellán;Andrés R. Masegosa

  • Disaggregated total uncertainty measure for credal sets

    Joaquín Abellán;George J. Klir;Serafín Moral

  • Uncertainty measures on probability intervals from the imprecise Dirichlet model

    Joaquín Abellán

  • Increasing diversity in random forest learning algorithm via imprecise probabilities

    Joaquín Abellán;Carlos J. Mantas;Javier G. Castellano;Serafín Moral-García

  • Some Variations on the PC Algorithm.

    Joaquín Abellán;Manuel Gómez-Olmedo;Serafín Moral

  • Bagging Decision Trees on Data Sets with Classification Noise

    Joaquín Abellán;Andrés R. Masegosa

  • An ensemble method using credal decision trees

    Joaquín Abellán;Andrés R. Masegosa

  • COMPLETING A TOTAL UNCERTAINTY MEASURE IN THE DEMPSTER-SHAFER THEORY

    Joaquín Abellán;Serafín Moral

  • Bagging of credal decision trees for imprecise classification

    Serafín Moral-García;Carlos Javier Mantas;Javier G. Castellano;María D. Benítez

  • Analysis and extension of decision trees based on imprecise probabilities: Application on noisy data

    Carlos J. Mantas;Joaquín Abellán

Frequent Co-Authors

Serafín Moral
Serafín Moral University of Granada
Frank P. A. Coolen
Frank P. A. Coolen Durham University
George J. Klir
George J. Klir Binghamton University

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