World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
51
Citations
18664
World Ranking
5211
National Ranking
2392

Stefano Lonardi 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 Stefano Lonardi 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: 163 publications — 32nd percentile

32% of scientists in this discipline score the same or lower.

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

Stefano Lonardi 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 Stefano Lonardi 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: 51 D-Index — 63rd percentile

63% of scientists in this discipline score the same or lower.

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

Research.com Recognitions

  • 2018 - Fellow of the American Association for the Advancement of Science (AAAS)
  • 2016 - ACM Distinguished Member
  • 2016 - IEEE Fellow For contributions to computational biology and data mining
  • 2014 - ACM Senior Member

Overview

Stefano Lonardi is affiliated with the University of California, Riverside in the United States. Their research spans fields including Biochemistry, Genetics and Molecular Biology, as well as Agricultural and Biological Sciences. The scientist's work particularly focuses on subfields such as Molecular Biology, Plant Science, Parasitology, Public Health, Environmental and Occupational Health, and Genetics.

Their research topics cover a range of areas including RNA and protein synthesis mechanisms, agricultural pest management studies, genomics and phylogenetic studies, CRISPR and genetic engineering, chromosomal and genetic variations, vector-borne infectious diseases, and RNA modifications and cancer.

Stefano Lonardi's recent publications demonstrate engagement with diverse biological and computational challenges. Notable recent papers include:

  • "Mustache: multi-scale detection of chromatin loops from Hi-C and Micro-C maps using scale-space representation," 2020, Genome Biology
  • "Genome-wide functional screens enable the prediction of high activity CRISPR-Cas9 and -Cas12a guides in Yarrowia lipolytica," 2022, Nature Communications
  • "A view of the pan-genome of domesticated Cowpea ( Vigna unguiculata [L.] Walp.)," 2023, The Plant Genome
  • "Karyotype variation, spontaneous genome rearrangements affecting chemical insensitivity, and expression level polymorphisms in the plant pathogen Phytophthora infestans revealed using its first chromosome-scale assembly," 2022, PLoS Pathogens
  • "Babesia duncani multi-omics identifies virulence factors and drug targets," 2023, Nature Microbiology

Frequent collaborators in their work include Karine G. Le Roch, Sakshar Chakravarty, Ian Wheeldon, Qihua Liang, and Timothy J. Close. Publication venues with multiple contributions include bioRxiv (Cold Spring Harbor Laboratory), Genome Biology, Genome Research, BMC Bioinformatics, and NAR Genomics and Bioinformatics.

Stefano Lonardi has received professional recognition such as being named a Fellow of the American Association for the Advancement of Science (AAAS) in 2018. They have also been honored as an ACM Distinguished Member in 2016, an IEEE Fellow the same year for contributions to computational biology and data mining, and an ACM Senior Member in 2014.

Best Publications

  • A symbolic representation of time series, with implications for streaming algorithms

    Jessica Lin;Eamonn Keogh;Stefano Lonardi;Bill Chiu

  • A Whole-Genome Assembly of Drosophila

    Eugene W. Myers;Granger G. Sutton;Art L. Delcher;Ian M. Dew

  • Experiencing SAX: a novel symbolic representation of time series

    Jessica Lin;Eamonn Keogh;Li Wei;Stefano Lonardi

  • A physical, genetic and functional sequence assembly of the barley genome

    Klaus F.X. Mayer;Robbie Waugh;Peter Langridge;Timothy J. Close

  • Towards parameter-free data mining

    Eamonn Keogh;Stefano Lonardi;Chotirat Ann Ratanamahatana

  • Probabilistic discovery of time series motifs

    Bill Chiu;Eamonn Keogh;Stefano Lonardi

  • CLARK: fast and accurate classification of metagenomic and genomic sequences using discriminative k-mers

    Rachid Ounit;Steve Wanamaker;Timothy J Close;Stefano Lonardi

  • Efficient and accurate construction of genetic linkage maps from the minimum spanning tree of a graph.

    Yonghui Wu;Prasanna R. Bhat;Timothy J. Close;Stefano Lonardi

  • Finding surprising patterns in a time series database in linear time and space

    Eamonn Keogh;Stefano Lonardi;Bill 'Yuan-chi' Chiu

  • Composition Profiler: a tool for discovery and visualization of amino acid composition differences

    Vladimir Vacic;Vladimir N Uversky;Vladimir N Uversky;A Keith Dunker;Stefano Lonardi

  • Comprehensive benchmarking and ensemble approaches for metagenomic classifiers.

    Alexa B. R. McIntyre;Rachid Ounit;Ebrahim Afshinnekoo;Ebrahim Afshinnekoo;Robert J. Prill

  • Mining motifs in massive time series databases

    P. Patel;E. Keogh;J. Lin;S. Lonardi

  • Mustache: multi-scale detection of chromatin loops from Hi-C and Micro-C maps using scale-space representation.

    Abbas Roayaei Ardakany;Abbas Roayaei Ardakany;Halil Tuvan Gezer;Halil Tuvan Gezer;Stefano Lonardi;Ferhat Ay;Ferhat Ay

  • Visually mining and monitoring massive time series

    Jessica Lin;Eamonn Keogh;Stefano Lonardi;Jeffrey P. Lankford

  • Time-series Bitmaps: a Practical Visualization Tool for Working with Large Time Series Databases.

    Nitin Kumar;Venkata Nishanth Lolla;Eamonn J. Keogh;Stefano Lonardi

  • Assignment of Orthologous Genes via Genome Rearrangement

    Xin Chen;Jie Zheng;Zheng Fu;Peng Nan

  • Assumption-free anomaly detection in time series

    Li Wei;Nitin Kumar;Venkata Lolla;Eamonn J. Keogh

  • Visualizing and discovering non-trivial patterns in large time series databases

    Jessica Lin;Eamonn Keogh;Stefano Lonardi

  • A novel bit level time series representation with implication of similarity search and clustering

    Chotirat Ratanamahatana;Eamonn Keogh;Anthony J. Bagnall;Stefano Lonardi

  • Compression-based data mining of sequential data

    Eamonn Keogh;Stefano Lonardi;Chotirat Ann Ratanamahatana;Li Wei

  • This Provisional PDF corresponds to the article as it appeared upon acceptance. Fully formatted PDF and full text (HTML) versions will be made available soon. Development and implementation of high-throughput SNP genotyping in barley

    Stefano Lonardi;Luke Ramsay;Steve Wanamaker;Mikeal L Roose

Frequent Co-Authors

Timothy J. Close
Timothy J. Close University of California, Riverside
Eamonn Keogh
Eamonn Keogh University of California, Riverside
Yonghui Wu
Yonghui Wu Google (United States)
Ming-Cheng Luo
Ming-Cheng Luo University of California, Davis
Gary J. Muehlbauer
Gary J. Muehlbauer University of Minnesota
Tao Jiang
Tao Jiang University of California, Riverside
Karine G. Le Roch
Karine G. Le Roch University of California, Riverside
Nils Stein
Nils Stein University of Western Australia
Philip A. Roberts
Philip A. Roberts University of California, Riverside
Frank M. You
Frank M. You Agriculture and Agriculture-Food Canada

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