World's Best Scientists 2026 revealed!

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Engineering and Technology

D-Index
41
Citations
9355
World Ranking
6829
National Ranking
1861

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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