World's Best Scientists 2026 revealed!

D-Index & Metrics

Biology and Biochemistry

D-Index
68
Citations
28077
World Ranking
7623
National Ranking
591

Computer Science

D-Index
61
Citations
22897
World Ranking
3000
National Ranking
180

Pietro Liò 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 Pietro Liò 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: 506 publications — 93rd percentile

93% of scientists in this discipline score the same or lower.

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

Pietro Liò 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 Pietro Liò 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: 61 D-Index — 79th percentile

79% of scientists in this discipline score the same or lower.

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

Overview

Pietro Liò is affiliated with the University of Cambridge in the United Kingdom. Their research spans multiple fields and subfields, primarily focusing on computer science and biochemistry, genetics, and molecular biology. Within these domains, Liò's work covers artificial intelligence, molecular biology, computer vision and pattern recognition, radiology, nuclear medicine and imaging, and computational theory and mathematics.

Their main research topics include advanced graph neural networks, explainable artificial intelligence (XAI), machine learning applications in healthcare, computational drug discovery methods, machine learning in materials science, bioinformatics and genomic networks, and topic modeling.

Recent publications by Pietro Liò include:

  • Common pitfalls and recommendations for using machine learning to detect and prognosticate for COVID-19 using chest radiographs and CT scans, 2020, Research Portal (King's College London)
  • Principal Neighbourhood Aggregation for Graph Nets, 2020, arXiv (Cornell University)
  • How artificial intelligence and machine learning can help healthcare systems respond to COVID-19, 2020, Machine Learning
  • Emotion Recognition From EEG Signal Focusing on Deep Learning and Shallow Learning Techniques, 2021, IEEE Access
  • A machine learning model to identify early stage symptoms of SARS-Cov-2 infected patients, 2020, Expert Systems with Applications

Pietro Liò frequently co-authors with a number of researchers, among them:

  • Mohammad Ali Moni
  • Pietro Barbiero
  • Mateja Jamnik
  • Ramón Viñas
  • Tiago Azevedo

Their publications are often found in venues such as:

  • arXiv (Cornell University)
  • bioRxiv (Cold Spring Harbor Laboratory)
  • Scientific Reports
  • Proceedings of the AAAI Conference on Artificial Intelligence
  • SSRN Electronic Journal

Best Publications

  • Graph Attention Networks

    Petar Veličković;Guillem Cucurull;Arantxa Casanova;Adriana Romero

  • Hematopoietic Stem Cells Reversibly Switch from Dormancy to Self-Renewal during Homeostasis and Repair

    Anne Wilson;Elisa Laurenti;Gabriela M. Oser;Richard C. van der Wath

  • Identifying the Best Machine Learning Algorithms for Brain Tumor Segmentation, Progression Assessment, and Overall Survival Prediction in the BRATS Challenge

    Spyridon Bakas;Mauricio Reyes;Andras Jakab;Stefan Bauer

  • The BioMart community portal: an innovative alternative to large, centralized data repositories

    Damian Smedley;Syed Haider;Steffen Durinck;Luca Pandini

  • Periodic gene expression program of the fission yeast cell cycle

    Gabriella Rustici;Juan Mata;Katja Kivinen;Pietro Lió

  • Deep Graph Infomax

    Petar Velickovic;William Fedus;William L. Hamilton;Pietro Liò

  • Molecular phylogenetics: state-of-the-art methods for looking into the past.

    Simon Whelan;Pietro Liò;Nick Goldman

  • Models of Molecular Evolution and Phylogeny

    Pietro Liò;Nick Goldman

  • Towards real-time community detection in large networks.

    Ian X. Y. Leung;Pan Hui;Pietro Liò;Jon Crowcroft

  • MeDuSa: a multi-draft based scaffolder

    Emanuele Bosi;Beatrice Donati;Marco Galardini;Sara Brunetti

  • A parameter-efficient deep learning approach to predict conversion from mild cognitive impairment to Alzheimer's disease.

    Simeon E. Spasov;Luca Passamonti;Andrea Duggento;Pietro Liò

  • Histidine biosynthetic pathway and genes: structure, regulation, and evolution.

    P Alifano;R Fani;P Liò;A Lazcano

  • Biometric evidence that sexual selection has shaped the hominin face.

    Eleanor M. Weston;Adrian E. Friday;Pietro Liò

  • Distinct Epigenomic Features in End-Stage Failing Human Hearts

    Mehregan Movassagh;Mun-Kit Choy;David A. Knowles;Lina Cordeddu

  • Predicting factors for survival of breast cancer patients using machine learning techniques

    Mogana Darshini Ganggayah;Nur Aishah Taib;Yip Cheng Har;Pietro Lio

  • Principal Neighbourhood Aggregation for Graph Nets

    Gabriele Corso;Luca Cavalleri;Dominique Beaini;Pietro Liò

  • Wavelets in bioinformatics and computational biology: state of art and perspectives.

    Pietro Liò

  • Collective human mobility pattern from taxi trips in urban area

    Chengbin Peng;Xiaogang Jin;Ka Chun Wong;Meixia Shi

  • Computational Modeling, Formal Analysis, and Tools for Systems Biology

    Ezio Bartocci;Pietro Lió

  • Towards Sparse Hierarchical Graph Classifiers.

    Catalina Cangea;Petar Velickovic;Nikola Jovanovic;Thomas Kipf

  • The glutamine 27 β2-adrenoceptor polymorphism is associated with elevated IgE levels in asthmatic families

    Dewar Jc;Wilkinson J;Wheatley A;Thomas Ns

Frequent Co-Authors

Renato Fani
Renato Fani University of Florence
Nicola Toschi
Nicola Toschi University of Rome Tor Vergata
Pan Hui
Pan Hui Hong Kong University of Science and Technology
Luca Passamonti
Luca Passamonti University of Cambridge
Jon Crowcroft
Jon Crowcroft University of Cambridge
Syed Haider
Syed Haider Institute of Cancer Research
Alessio Papini
Alessio Papini University of Florence
Nick Goldman
Nick Goldman European Bioinformatics Institute
Nicholas D. Lane
Nicholas D. Lane University of Cambridge
Anne Wilson
Anne Wilson University of Lausanne

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