World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
34
Citations
5836
World Ranking
12068
National Ranking
470

Lila Kari 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 Lila Kari 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: 250 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: 560 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: 424 scientists 242–251 publications: 408 scientists 252–261 publications: 378 scientists 262–271 publications: 300 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: 242 publications — 60th percentile

60% of scientists in this discipline score the same or lower.

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

Lila Kari 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 Lila Kari sits on this spectrum.

30–31 D-Index: 879 scientists 32–33 D-Index: 984 scientists 34–35 D-Index: 918 scientists 36–37 D-Index: 990 scientists 38–39 D-Index: 969 scientists 40–41 D-Index: 907 scientists 42–43 D-Index: 821 scientists 44–45 D-Index: 765 scientists 46–47 D-Index: 689 scientists 48–49 D-Index: 543 scientists 50–51 D-Index: 543 scientists 52–53 D-Index: 517 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: 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.

Overview

Lila Kari is affiliated with the University of Waterloo in Canada and has a research portfolio spanning the fields of Biochemistry, Genetics and Molecular Biology as well as Computer Science. Their work integrates concepts from molecular biology and computational theory to address complex biological problems.

The scientist's main research fields include:

  • Biochemistry, Genetics and Molecular Biology
  • Computer Science

Within these fields, Kari has contributed to subfields such as:

  • Molecular Biology
  • Computational Theory and Mathematics
  • Artificial Intelligence
  • Computer Networks and Communications
  • Infectious Diseases

Their primary topics of research concentrate on genomic and bioinformatics challenges, including:

  • Genomics and Phylogenetic Studies
  • Machine Learning in Bioinformatics
  • Fractal and DNA sequence analysis
  • DNA and Biological Computing
  • Semigroups and Automata Theory
  • Advanced Graph Theory Research
  • Algorithms and Data Compression

Lila Kari's frequent publication venues reflect this interdisciplinary approach, with notable contributions appearing in:

  • Theoretical Computer Science
  • bioRxiv (Cold Spring Harbor Laboratory)
  • arXiv (Cornell University)
  • PLoS ONE
  • Bioinformatics

Significant recent papers illustrate the blend of computational and biological research:

  • "Machine learning using intrinsic genomic signatures for rapid classification of novel pathogens: COVID-19 case study," 2020, PLoS ONE
  • "Machine learning using intrinsic genomic signatures for rapid classification of novel pathogens: COVID-19 case study," 2020, bioRxiv (Cold Spring Harbor Laboratory)
  • "DeLUCS: Deep learning for unsupervised clustering of DNA sequences," 2022, PubMed Central
  • "Environment and taxonomy shape the genomic signature of prokaryotic extremophiles," 2023, Scientific Reports
  • "As good as it gets: a scaling comparison of DNA computing, network biocomputing, and electronic computing approaches to an NP-complete problem," 2021, New Journal of Physics

Kari frequently collaborates with other researchers, with the following being common coauthors in their work:

  • Kathleen A. Hill
  • Gurjit S. Randhawa
  • Pablo Millán Arias
  • Maximillian P. M. Soltysiak
  • Fatemeh Alipour

Best Publications

  • Machine learning using intrinsic genomic signatures for rapid classification of novel pathogens: COVID-19 case study.

    Gurjit S. Randhawa;Maximillian P. M. Soltysiak;Hadi El Roz;Camila P. E. de Souza

  • The many facets of natural computing

    Lila Kari;Grzegorz Rozenberg

  • The evolution of cellular computing: nature’s solution to a computational problem

    Laura F Landweber;Lila Kari

  • Contextual Insertions/Deletions and Computability

    Lila Kari;Gabriel Thierrin

  • DNA computing, sticker systems, and universality ?

    Lila Kari;Gheorghe Păun;Grzegorz Rozenberg;Arto Salomaa

  • Computationally universal P systems without priorities: two catalysts are sufficient

    Rudolf Freund;Lila Kari;Marion Oswald;Petr Sosík

  • DNA Computing Based on Splicing: The Existence of Universal Computers

    Rudolf Freund;Lila Kari;Gheorghe Paun

  • Theory of Evolutionary Computation: Recent Developments in Discrete Optimization

    Unknown

  • The spectrum of genomic signatures: from dinucleotides to chaos game representation

    Yingwei Wang;Kathleen Hill;Shiva Singh;Lila Kari

  • Test Tube Distributed Systems Based on Splicing

    Erzsébet Csuhaj-Varjú;Lila Kari;Gheorghe Paun

  • L Systems

    Lila Kari;Grzegorz Rozenberg;Arto Salomaa

  • Coding properties of DNA languages

    Salah Hussini;Lila Kari;Stavros Konstantinidis

  • Universal Molecular Computation in Ciliates

    Laura F. Landweber;Lila Kari

  • An open-source k-mer based machine learning tool for fast and accurate subtyping of HIV-1 genomes.

    Stephen Solis-Reyes;Mariano Avino;Art Poon;Lila Kari

  • At the crossroads of DNA computing and formal languages: Characterizing recursively enumerable languages using insertion-deletion systems.

    Lila Kari;Gheorghe Paun;Gabriel Thierrin;Sheng Yu

  • DNA computing based on splicing: universality results.

    Csuhaj-Varjú E;Freund R;Kari L;Păun G

  • Using DNA to solve the bounded Post correspondence problem

    Lila Kari;Greg Gloor;Sheng Yu

  • On language equations with invertible operations

    Lila Kari

  • On a special class of primitive words

    Elena Czeizler;Lila Kari;Shinnosuke Seki

  • Computational power of gene rearrangement.

    Lila Kari;Laura F. Landweber

  • On the decidability of self-assembly of infinite ribbons

    L. Adleman;J. Kari;L. Kari;D. Reishus

Frequent Co-Authors

Gheorghe Paun
Gheorghe Paun Romanian Academy
Arto Salomaa
Arto Salomaa Turku Centre for Computer Science
Oscar H. Ibarra
Oscar H. Ibarra University of California, Santa Barbara
Grzegorz Rozenberg
Grzegorz Rozenberg Leiden University
Laura F. Landweber
Laura F. Landweber Columbia University
Gregory B. Gloor
Gregory B. Gloor University of Western Ontario
Leonard M. Adleman
Leonard M. Adleman University of Southern California
Przemyslaw Prusinkiewicz
Przemyslaw Prusinkiewicz University of Calgary
Donald Sannella
Donald Sannella University of Edinburgh
Koji Nakano
Koji Nakano Hiroshima University

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