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Luca Martino

D-Index & Metrics

Discipline name D-Index World Ranking Current World Ranking National Ranking Current National Ranking Publications Citations
Computer Science 34 12259 11902 219 217 185 4269

Luca Martino publications per year

The chart shows the history of publications by Luca Martino between 2001 and 2026, highlighting the no. of papers published in each year and offering an overview of the publication velocity of this scholar. Luca Martino published across 26 years, from 2001 to 2026, averaging 9.4 papers a year. Output peaked at 28 publications in 2015. 15 of the 244 publications appeared in the last two years.

No. of publications
5 10 15 20 25
Bar chart. Horizontal axis: year, 2001 to 2026. Vertical axis: number of publications, 0 to 28. Peak 28 publications in 2015. 2001: 1 publication 2002: 0 publications 2003: 0 publications 2004: 0 publications 2005: 0 publications 2006: 1 publication 2007: 0 publications 2008: 0 publications 2009: 5 publications 2010: 2 publications 2011: 3 publications 2012: 8 publications 2013: 10 publications 2014: 12 publications 2015: 28 publications 2016: 21 publications 2017: 26 publications 2018: 25 publications 2019: 10 publications 2020: 23 publications 2021: 22 publications 2022: 10 publications 2023: 10 publications 2024: 12 publications 2025: 13 publications 2026: 2 publications
2001 2026

244 publications in total across all disciplines

View publications per year as a table
Luca Martino: publications per year, 2001 to 2026
Year Publications
2001 1
2002 0
2003 0
2004 0
2005 0
2006 1
2007 0
2008 0
2009 5
2010 2
2011 3
2012 8
2013 10
2014 12
2015 28
2016 21
2017 26
2018 25
2019 10
2020 23
2021 22
2022 10
2023 10
2024 12
2025 13
2026 2
Total 244
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Luca Martino 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 Luca Martino sits on this spectrum.

No. of scientists
200 400 600
Bar chart with 97 bars. Horizontal axis: publications, 32–41 to 991+. Vertical axis: number of scientists, 0 to 609. Most scientists, 609, have 142–151 publications. The last bar groups every scientist with 991 publications or more. The highlighted bar, 182–191 publications, is where this scientist sits. 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
32–41 publications 991+

This scientist: 185 publications — 41st percentile

41% of scientists in this discipline score the same or lower.

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

View publications distribution as a table
Number of Computer Science scientists by publication count, Research.com 2026 ranking edition. Based on 14,188 ranked scientists.
Publications Scientists This scientist
32–41 7
42–51 22
52–61 82
62–71 134
72–81 249
82–91 324
92–101 421
102–111 420
112–121 497
122–131 544
132–141 555
142–151 609
152–161 559
162–171 534
172–181 556
182–191 583 185
192–201 519
202–211 508
212–221 490
222–231 437
232–241 423
242–251 408
252–261 377
262–271 301
272–281 335
282–291 320
292–301 293
302–311 250
312–321 238
322–331 206
332–341 209
342–351 208
352–361 162
362–371 176
372–381 127
382–391 158
392–401 128
402–411 104
412–421 94
422–431 99
432–441 83
442–451 108
452–461 73
462–471 77
472–481 69
482–491 84
492–501 62
502–511 54
512–521 57
522–531 51
532–541 51
542–551 32
552–561 38
562–571 28
572–581 43
582–591 33
592–601 41
602–611 32
612–621 28
622–631 25
632–641 27
642–651 17
652–661 20
662–671 17
672–681 15
682–691 14
692–701 21
702–711 13
712–721 12
722–731 19
732–741 14
742–751 12
752–761 10
762–771 10
772–781 11
782–791 10
792–801 11
802–811 8
812–821 8
822–831 7
832–841 11
842–851 10
852–861 5
862–871 9
872–881 4
882–891 6
892–901 3
902–911 6
912–921 3
922–931 2
932–941 2
942–951 2
952–961 3
962–971 3
972–981 3
982–990 5
991+ 100
Download as CSV

Luca Martino 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 Luca Martino sits on this spectrum.

No. of scientists
200 400 600 800
Bar chart with 52 bars. Horizontal axis: D-Index, 30–31 to 131+. Vertical axis: number of scientists, 0 to 990. Most scientists, 990, have 36–37 D-Index. The last bar groups every scientist with 131 D-Index or more. The highlighted bar, 34–35 D-Index, is where this scientist sits. 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
30–31 D-Index 131+

This scientist: 34 D-Index — 16th percentile

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

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

View D-Index distribution as a table
Number of Computer Science scientists by D-index, Research.com 2026 ranking edition. Based on 14,188 ranked scientists.
D-Index Scientists This scientist
30–31 879
32–33 983
34–35 918 34
36–37 990
38–39 968
40–41 907
42–43 821
44–45 763
46–47 689
48–49 543
50–51 543
52–53 518
54–55 500
56–57 458
58–59 400
60–61 337
62–63 308
64–65 292
66–67 249
68–69 213
70–71 192
72–73 189
74–75 165
76–77 139
78–79 119
80–81 121
82–83 113
84–85 88
86–87 87
88–89 75
90–91 69
92–93 57
94–95 46
96–97 38
98–99 34
100–101 36
102–103 27
104–105 37
106–107 18
108–109 31
110–111 19
112–113 16
114–115 12
116–117 20
118–119 15
120–121 5
122–123 20
124–125 8
126–127 5
128–129 7
130 3
131+ 98
Download as CSV

Overview

Luca Martino is affiliated with King Juan Carlos University in Spain and has contributed extensively to the field of computer science, focusing on areas such as artificial intelligence and statistics and probability. Their research spans across related subfields including statistics, probability and uncertainty, signal processing, and global and planetary change.

The scientist's work particularly emphasizes topics such as Gaussian processes and Bayesian inference, probabilistic and robust engineering design, and target tracking and data fusion in sensor networks. Additional research interests include Bayesian methods and mixture models, statistical methods and inference, Markov chains and Monte Carlo methods, as well as statistical methods and Bayesian inference.

Martino has published multiple research papers across various scientific venues. Some of their recent works include:

  • A Joint introduction to Gaussian Processes and Relevance Vector Machines with Connections to Kalman filtering and other Kernel Smoothers, 2020, arXiv (Cornell University)
  • A Survey of Active Learning for Quantifying Vegetation Traits from Terrestrial Earth Observation Data, 2021, Remote Sensing
  • Rethinking the Effective Sample Size, 2022, International Statistical Review
  • Marginal Likelihood Computation for Model Selection and Hypothesis Testing: An Extensive Review, 2023, SIAM Review
  • Importance Gaussian Quadrature, 2020, IEEE Transactions on Signal Processing

The scientist frequently collaborates with other researchers, including Fernando Llorente, David Delgado-Gómez, Víctor Elvira, Ernesto Curbelo, and Gustau Camps-Valls. These collaborations have resulted in numerous coauthored publications.

Luca Martino's research is published predominantly in venues such as arXiv (Cornell University), Mathematics, IEEE Transactions on Geoscience and Remote Sensing, Computational Statistics, and SSRN Electronic Journal. Their work reflects a broad engagement with both theoretical and applied aspects of computer science, with a focus on statistical and probabilistic methodologies.

Best Publications

  • Moving Fast with Software Verification

    Cristiano Calcagno;Dino Distefano;Jérémy Dubreil;Dominik Gabi

  • Adaptive Importance Sampling: The past, the present, and the future

    Monica F. Bugallo;Victor Elvira;Luca Martino;David Luengo

  • Effective sample size for importance sampling based on discrepancy measures

    Luca Martino;Víctor Elvira;Francisco Louzada

  • A survey of Monte Carlo methods for parameter estimation

    David Luengo;Luca Martino;Luca Martino;Mónica F. Bugallo;Victor Elvira

  • Cooperative parallel particle filters for online model selection and applications to urban mobility

    Luca Martino;Jesse Read;Jesse Read;Víctor Elvira;Francisco Louzada

  • Efficient monte carlo methods for multi-dimensional learning with classifier chains

    Jesse Read;Luca Martino;David Luengo

  • Independent Doubly Adaptive Rejection Metropolis Sampling Within Gibbs Sampling

    Luca Martino;Jesse Read;David Luengo

  • Generalized Multiple Importance Sampling

    Víctor Elvira;Luca Martino;David Luengo;Mónica F. Bugallo

  • Improving population Monte Carlo

    Víctor Elvira;Luca Martino;David Luengo;Mónica F. Bugallo

  • A Survey of Active Learning for Quantifying Vegetation Traits from Terrestrial Earth Observation Data

    Katja Berger;Juan Pablo Rivera Caicedo;Luca Martino;Matthias Wocher

  • An Adaptive Population Importance Sampler: Learning From Uncertainty

    Luca Martino;Victor Elvira;David Luengo;Jukka Corander

  • Layered adaptive importance sampling

    L. Martino;V. Elvira;D. Luengo;J. Corander

  • Scalable multi-output label prediction

    Jesse Read;Luca Martino;Pablo M. Olmos;David Luengo

  • Physics-aware Gaussian processes in remote sensing

    Gustau Camps-Valls;Luca Martino;Daniel H. Svendsen;Manuel Campos-Taberner

  • Orthogonal parallel MCMC methods for sampling and optimization

    Luca Martino;Víctor Elvira;David Luengo;Jukka Corander

  • Generalized Multiple Importance Sampling

    Víctor Elvira;Luca Martino;David Luengo;Mónica F. Bugallo

  • Marginal likelihood computation for model selection and hypothesis testing: an extensive review.

    Fernando Llorente;Luca Martino;David Delgado;Javier López-Santiago

  • Adaptive importance sampling in signal processing

    Mónica F. Bugallo;Luca Martino;Jukka Corander

  • A Review of Multiple Try MCMC Algorithms for Signal Processing

    Luca Martino;Luca Martino

  • Marginal Likelihood Computation for Model Selection and Hypothesis Testing: an Extensive Review

    F. Llorente;L. Martino;D. Delgado;J. Lopez-Santiago

  • Efficient Multiple Importance Sampling Estimators

    Victor Elvira;Luca Martino;David Luengo;Monica F. Bugallo

  • Group Importance Sampling for particle filtering and MCMC

    Luca Martino;Luca Martino;Víctor Elvira;Gustau Camps-Valls

  • A Joint introduction to Gaussian Processes and Relevance Vector Machines with Connections to Kalman filtering and other Kernel Smoothers

    Luca Martino;Jesse Read

  • Advances in Importance Sampling

    Víctor Elvira;Luca Martino

  • Layered Adaptive Importance Sampling

    L. Martino;V. Elvira;D. Luengo;J. Corander

  • Improving Population Monte Carlo: Alternative Weighting

    Luca Martino;David Luengo;F. Bugallo

Frequent Co-Authors

Jesse Read
Jesse Read École Polytechnique
Francisco Louzada
Francisco Louzada Universidade de São Paulo
Gustau Camps-Valls
Gustau Camps-Valls University of Valencia
Jukka Corander
Jukka Corander University of Oslo
Jordi Muñoz-Marí
Jordi Muñoz-Marí University of Valencia
Jochem Verrelst
Jochem Verrelst University of Valencia
Petar M. Djuric
Petar M. Djuric Stony Brook University
Luis Alonso
Luis Alonso Universitat Politècnica de Catalunya
Jose Moreno
Jose Moreno University of Valencia
Steven W. Running
Steven W. Running University of Montana

External Links

Personal website of Luca Martino

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Best Scientists Citing Luca Martino

Jochem Verrelst

Jochem Verrelst

University of Valencia

Publications: 13

Gustau Camps-Valls

Gustau Camps-Valls

University of Valencia

Publications: 10

Jesse Read

Jesse Read

École Polytechnique

Publications: 9

Petar M. Djuric

Petar M. Djuric

Stony Brook University

Publications: 8

Christian P. Robert

Christian P. Robert

Paris Dauphine University

Publications: 7

Juan M. Corchado

Juan M. Corchado

University of Salamanca

Publications: 6

Min-Ling Zhang

Min-Ling Zhang

Southeast University

Publications: 6

Simo Särkkä

Simo Särkkä

Aalto University

Publications: 6

Mateu Sbert

Mateu Sbert

University of Girona

Publications: 6

Qingming Huang

Qingming Huang

University of Chinese Academy of Sciences

Publications: 5

Guorong Li

Guorong Li

University of Chinese Academy of Sciences

Publications: 5

Jose Moreno

Jose Moreno

University of Valencia

Publications: 5

Aki Vehtari

Aki Vehtari

Aalto University

Publications: 4

Yee Whye Teh

Yee Whye Teh

University of Oxford

Publications: 4

Constantine Kotropoulos

Constantine Kotropoulos

Aristotle University of Thessaloniki

Publications: 4

Alex A. Freitas

Alex A. Freitas

University of Kent

Publications: 4

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