World's Best Scientists 2026 revealed!

D-Index & Metrics

Engineering and Technology

D-Index
41
Citations
9355
World Ranking
6832
National Ranking
1862

Zoltán Toroczkai publication distribution in Engineering and Technology in 2026

The chart shows the distribution of publications by all Research.com ranked scientists in the field of Engineering and Technology in 2026. The highlighted bar marks where Zoltán Toroczkai sits on this spectrum.

38–47 publications: 20 scientists 48–57 publications: 35 scientists 58–67 publications: 96 scientists 68–77 publications: 135 scientists 78–87 publications: 190 scientists 88–97 publications: 259 scientists 98–107 publications: 283 scientists 108–117 publications: 369 scientists 118–127 publications: 341 scientists 128–137 publications: 386 scientists 138–147 publications: 372 scientists 148–157 publications: 457 scientists 158–167 publications: 415 scientists 168–177 publications: 407 scientists 178–187 publications: 421 scientists 188–197 publications: 378 scientists 198–207 publications: 403 scientists 208–217 publications: 317 scientists 218–227 publications: 346 scientists 228–237 publications: 321 scientists 238–247 publications: 260 scientists 248–257 publications: 280 scientists 258–267 publications: 240 scientists 268–277 publications: 214 scientists 278–287 publications: 242 scientists 288–297 publications: 203 scientists 298–307 publications: 166 scientists 308–317 publications: 154 scientists 318–327 publications: 175 scientists 328–337 publications: 159 scientists 338–347 publications: 99 scientists 348–357 publications: 131 scientists 358–367 publications: 106 scientists 368–377 publications: 118 scientists 378–387 publications: 97 scientists 388–397 publications: 108 scientists 398–407 publications: 82 scientists 408–417 publications: 71 scientists 418–427 publications: 64 scientists 428–437 publications: 55 scientists 438–447 publications: 54 scientists 448–457 publications: 60 scientists 458–467 publications: 47 scientists 468–477 publications: 40 scientists 478–487 publications: 30 scientists 488–497 publications: 29 scientists 498–507 publications: 38 scientists 508–517 publications: 40 scientists 518–527 publications: 32 scientists 528–537 publications: 23 scientists 538–547 publications: 28 scientists 548–557 publications: 23 scientists 558–567 publications: 19 scientists 568–577 publications: 16 scientists 578–587 publications: 17 scientists 588–597 publications: 18 scientists 598–607 publications: 22 scientists 608–617 publications: 15 scientists 618–627 publications: 9 scientists 628–637 publications: 11 scientists 638–647 publications: 21 scientists 648–657 publications: 12 scientists 658–667 publications: 9 scientists 668–677 publications: 11 scientists 678–687 publications: 9 scientists 688–697 publications: 6 scientists 698–707 publications: 14 scientists 708–717 publications: 7 scientists 718–727 publications: 8 scientists 728–737 publications: 10 scientists 738–747 publications: 9 scientists 748–757 publications: 5 scientists 758–767 publications: 5 scientists 768–777 publications: 11 scientists 778–787 publications: 7 scientists 788–797 publications: 2 scientists 798–803 publications: 4 scientists 804+ publications: 100 scientists
38 publications 804+

This scientist: 141 publications — 23rd percentile

23% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 804 publications or more.

Zoltán Toroczkai D-index placement in Engineering and Technology in 2026

The chart shows the D-index (discipline H-index) distribution of Engineering and Technology scientists ranked by Research.com in 2026. The highlighted bar marks where Zoltán Toroczkai sits on this spectrum.

30 D-Index: 59 scientists 31 D-Index: 114 scientists 32 D-Index: 129 scientists 33 D-Index: 189 scientists 34 D-Index: 200 scientists 35 D-Index: 262 scientists 36 D-Index: 311 scientists 37 D-Index: 312 scientists 38 D-Index: 350 scientists 39 D-Index: 385 scientists 40 D-Index: 348 scientists 41 D-Index: 362 scientists 42 D-Index: 426 scientists 43 D-Index: 380 scientists 44 D-Index: 310 scientists 45 D-Index: 341 scientists 46 D-Index: 301 scientists 47 D-Index: 306 scientists 48 D-Index: 271 scientists 49 D-Index: 246 scientists 50 D-Index: 210 scientists 51 D-Index: 253 scientists 52 D-Index: 213 scientists 53 D-Index: 221 scientists 54 D-Index: 195 scientists 55 D-Index: 186 scientists 56 D-Index: 170 scientists 57 D-Index: 167 scientists 58 D-Index: 166 scientists 59 D-Index: 144 scientists 60 D-Index: 152 scientists 61 D-Index: 141 scientists 62 D-Index: 138 scientists 63 D-Index: 131 scientists 64 D-Index: 118 scientists 65 D-Index: 114 scientists 66 D-Index: 119 scientists 67 D-Index: 95 scientists 68 D-Index: 87 scientists 69 D-Index: 77 scientists 70 D-Index: 89 scientists 71 D-Index: 69 scientists 72 D-Index: 54 scientists 73 D-Index: 46 scientists 74 D-Index: 55 scientists 75 D-Index: 54 scientists 76 D-Index: 49 scientists 77 D-Index: 53 scientists 78 D-Index: 46 scientists 79 D-Index: 28 scientists 80 D-Index: 39 scientists 81 D-Index: 36 scientists 82 D-Index: 24 scientists 83 D-Index: 26 scientists 84 D-Index: 36 scientists 85 D-Index: 18 scientists 86 D-Index: 25 scientists 87 D-Index: 19 scientists 88 D-Index: 26 scientists 89 D-Index: 27 scientists 90 D-Index: 23 scientists 91 D-Index: 15 scientists 92 D-Index: 12 scientists 93 D-Index: 9 scientists 94 D-Index: 15 scientists 95 D-Index: 10 scientists 96 D-Index: 13 scientists 97 D-Index: 13 scientists 98 D-Index: 9 scientists 99 D-Index: 7 scientists 100 D-Index: 7 scientists 101 D-Index: 8 scientists 102 D-Index: 7 scientists 103 D-Index: 7 scientists 104 D-Index: 9 scientists 105 D-Index: 6 scientists 106 D-Index: 9 scientists 107+ D-Index: 99 scientists
30 D-Index 107+

This scientist: 41 D-Index — 31st percentile

31% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 107 D-Index or more.

Research.com Recognitions

  • 2012 - Fellow of American Physical Society (APS) Citation For his contributions to the understanding the statistical physics of complex systems, in particular for his discoveries pertaining to the structure and dynamics of complex networks

Overview

Zoltán Toroczkai is affiliated with the University of Notre Dame in the United States and conducts research primarily in the fields of Computer Science and Physics and Astronomy. Their work spans various subfields including Artificial Intelligence, Cognitive Neuroscience, Statistical and Nonlinear Physics, Electrical and Electronic Engineering, and Computational Theory and Mathematics.

The scientist's research covers a range of topics, with notable focus areas including:

  • Complex Network Analysis Techniques
  • Quantum Computing Algorithms and Architecture
  • Neural dynamics and brain function
  • Functional Brain Connectivity Studies
  • Graph theory and applications
  • Neural Networks and Reservoir Computing
  • Advanced Neuroimaging Techniques and Applications

Among their recent publications are:

  • "An Ising Hamiltonian solver based on coupled stochastic phase-transition nano-oscillators," 2021, published in Nature Electronics
  • "Neuroscience Needs Network Science," 2023, Journal of Neuroscience
  • "Degree-preserving network growth," 2021, Nature Physics
  • "Is stochastic thermodynamics the key to understanding the energy costs of computation?," 2024, Proceedings of the National Academy of Sciences
  • "Accelerating a continuous-time analog SAT solver using GPUs," 2020, Computer Physics Communications

Their frequent publication venues include:

  • arXiv (Cornell University)
  • Nature Physics
  • bioRxiv (Cold Spring Harbor Laboratory)
  • Nature Electronics
  • Journal of Neuroscience

Collaborations are a significant aspect of their research activity. Frequent co-authors include:

  • Shubha R. Kharel
  • Tamás Róbert Mezei
  • Péter L. Erdős
  • Arijit Raychowdhury
  • Sourav Dutta

The scientist was recognized as a Fellow of the American Physical Society (APS) in 2012 for contributions to understanding the statistical physics of complex systems, particularly regarding the structure and dynamics of complex networks.

Best Publications

  • Modelling disease outbreaks in realistic urban social networks.

    Stephen Eubank;Hasan Guclu;V. S. Anil Kumar;Madhav V. Marathe

  • Cortical High-Density Counterstream Architectures

    Nikola T. Markov;Nikola T. Markov;Nikola T. Markov;Mária Ercsey-Ravasz;David C. Van Essen;Kenneth Knoblauch;Kenneth Knoblauch

  • A Predictive Network Model of Cerebral Cortical Connectivity Based on a Distance Rule

    Mária Ercsey-Ravasz;Mária Ercsey-Ravasz;Nikola T. Markov;Nikola T. Markov;Nikola T. Markov;Camille Lamy;Camille Lamy;David C. Van Essen

  • Weight Consistency Specifies Regularities of Macaque Cortical Networks

    N. T. Markov;N. T. Markov;P. Misery;P. Misery;Arnaud Falchier;Arnaud Falchier;C. Lamy;C. Lamy

  • Complexity of the International Agro-Food Trade Network and Its Impact on Food Safety

    Mária Ercsey-Ravasz;Zoltán Toroczkai;Zoltán Lakner;József Baranyi

  • Network dynamics: Jamming is limited in scale-free systems

    Zoltán Toroczkai;Kevin E. Bassler

  • The role of long-range connections on the specificity of the macaque interareal cortical network.

    Nikola T. Markov;Maria Ercsey-Ravasz;Maria Ercsey-Ravasz;Camille Lamy;Camille Lamy;Ana Rita Ribeiro Gomes;Ana Rita Ribeiro Gomes

  • Spatial Embedding and Wiring Cost Constrain the Functional Layout of the Cortical Network of Rodents and Primates.

    Szabolcs Horvát;Răzvan Gămănuț;Mária Ercsey-Ravasz;Loïc Magrou

  • Quantifying randomness in real networks.

    Chiara Orsini;Marija M. Dankulov;Marija M. Dankulov;Pol Colomer-de-Simón;Almerima Jamakovic

  • Efficient and Exact Sampling of Simple Graphs with Given Arbitrary Degree Sequence

    Charo I. Del Genio;Charo I. Del Genio;Hyunju Kim;Zoltán Toroczkai;Kevin E. Bassler;Kevin E. Bassler

  • Suppressing roughness of virtual times in parallel discrete-event simulations.

    György Korniss;Mark A. Novotny;Hasan Guclu;Zoltán Toroczkai

  • Predicting commuter flows in spatial networks using a radiation model based on temporal ranges.

    Yihui Ren;Mária Ercsey-Ravasz;Pu Wang;Marta C. González

  • Competition-Driven Network Dynamics: Emergence of a Scale-Free Leadership Structure and Collective Efficiency

    M. Anghel;Zoltán Toroczkai;Kevin E. Bassler;G. Korniss

  • Chaotic flow: the physics of species coexistence.

    György Károlyi;Áron Péntek;István Scheuring;Tamás Tél

  • Structural bottlenecks for communication in networks.

    Sameet Sreenivasan;Sameet Sreenivasan;Reuven Cohen;Eduardo López;Zoltán Toroczkai;Zoltán Toroczkai

  • An Ising Hamiltonian solver based on coupled stochastic phase-transition nano-oscillators

    S. Dutta;A. Khanna;A. S. Assoa;H. Paik

  • Optimization hardness as transient chaos in an analog approach to constraint satisfaction

    Mária Ercsey-Ravasz;Zoltán Toroczkai

  • Advection of active particles in open chaotic flows

    Zoltán Toroczkai;Zoltán Toroczkai;György Károlyi;Áron Péntek;Tamás Tél

  • From Massively Parallel Algorithms and Fluctuating Time Horizons to Nonequilibrium Surface Growth

    György Korniss;Zoltán Toroczkai;Zoltán Toroczkai;Mark A. Novotny;Per Arne Rikvold

  • Proximity networks and epidemics

    Zoltán Toroczkai;Zoltán Toroczkai;Hasan Guclu

Frequent Co-Authors

Kenneth Knoblauch
Kenneth Knoblauch Claude Bernard University Lyon 1
Celso Grebogi
Celso Grebogi University of Aberdeen
S. Das Sarma
S. Das Sarma University of Maryland, College Park
David C. Van Essen
David C. Van Essen Washington University in St. Louis
Pascal Barone
Pascal Barone Federal University of Toulouse Midi-Pyrénées
Xiaobo Sharon Hu
Xiaobo Sharon Hu University of Notre Dame
Jerome Sallet
Jerome Sallet University of Oxford
Dmitri Krioukov
Dmitri Krioukov Northeastern University

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