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Laurent Hebert-Dufresne

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Laurent Hebert-Dufresne
NationalityCanadian
OccupationProfessor of Computer Science
EmployerUniversity of Vermont
Known forNetwork science, complex contagion modeling, computational epidemiology
Alma materUniversité Laval

Laurent Hebert-Dufresne is a professor of computer science at the University of Vermont, where his research centers on network science and the mathematical modeling of complex systems.[1] His work spans the study of interacting contagions, epidemic modeling, and the structure and dynamics of complex networks, and he has contributed to interdisciplinary research connecting mathematics, biology, and computational social science.[2] Over the course of his career he has authored or co-authored 98 papers that have collectively been cited more than 2,800 times, and he holds an h-index of 30 according to bibliometric data compiled by Semantic Scholar.[3] Colleagues and collaborators describe his research program as one that bridges theoretical network science with pressing applied questions in public health and information dynamics.

Education

Hebert-Dufresne completed a Master of Science in physics at Universite Laval in 2011 and a Ph.D. in physics at the same institution in 2014.[4] He was subsequently a James S. McDonnell Foundation Fellow at the Santa Fe Institute and a researcher at the Institute for Disease Modeling before joining the University of Vermont.[4]

Career

Hebert-Dufresne joined the faculty of the University of Vermont, where he holds an appointment in the Department of Computer Science and is affiliated with the university's Complex Systems Center and Vermont Complex Systems Institute.[5] At UVM he has built a research group focused on network science, mathematical epidemiology, and computational approaches to social and biological systems.[6]

Prior to and during his time at UVM, Hebert-Dufresne maintained a research affiliation with the Santa Fe Institute, a research institution dedicated to the study of complex systems.[7] This affiliation supported early work on network comparison methods that would later be extended through subsequent grant-funded research conducted at the University of Vermont.[8]

His research career has been supported by federal funding agencies, including the National Science Foundation and the National Institutes of Health. Hebert-Dufresne received two NSF awards under the project title "Network Comparison, a Cornerstone of the Foundations of Network Science," totaling $253,672. The first award, for $125,000, was granted to the Santa Fe Institute on August 23, 2016, and the second, for $128,672, was granted to the University of Vermont and State Agricultural College on May 16, 2018.[9] These grants supported theoretical and computational work aimed at developing rigorous methods for comparing network structures across disciplines, a foundational problem in network science.[10]

He has also received support from the National Institutes of Health for a series of projects titled "Mathematical, Computational, and Predictive Modeling Core," administered through the University of Vermont and State Agricultural College. Across the four listed NIH funding periods, these projects received a combined total of $860,474, with individual award amounts of $209,420, $208,419, and $224,036 documented in NIH funding records.[11] This funding has supported infrastructure for mathematical and computational modeling relevant to public health research conducted at the University of Vermont.[12]

Throughout his career, Hebert-Dufresne has collaborated with researchers across computer science, mathematics, epidemiology, and computational social science, contributing to a body of published work that addresses both theoretical questions in network science and applied problems in epidemic modeling and online information dynamics.[13]

Research

Hebert-Dufresne's research addresses the mathematical and computational modeling of complex systems, with particular emphasis on networks, contagion processes, and the interaction between multiple simultaneous spreading phenomena.[14] A recurring theme in his work is the study of how diseases, beliefs, behaviors, and narratives can interact and co-spread through populations, a topic addressed directly in his 2025 review article "One pathogen does not an epidemic make: A review of interacting contagions, diseases, beliefs, and stories," published in arXiv.org.[15]

His 2024 paper "The path of complexity," published in npj Complexity, has been cited 17 times and reflects his continued engagement with foundational questions in complexity science, examining the historical and conceptual development of complexity as a field of study.[16] In the same year, he contributed to "Biomedical open source software: Crucial packages and hidden heroes," published in PLoS Computational Biology, which examines the software infrastructure underlying biomedical research and has been cited 4 times.[17]

Hebert-Dufresne has also published extensively on epidemic modeling and public health policy. His 2023 paper "Temporal and Probabilistic Comparisons of Epidemic Interventions," published in the Bulletin of Mathematical Biology, examines methods for comparing the timing and effectiveness of different public health interventions and has been cited 3 times.[18] Related work published the same year, "The unintended consequences of inconsistent closure policies and mobility restrictions during epidemics," appeared in BMC Global and Public Health and has been cited 4 times, addressing how inconsistent policy implementation across jurisdictions can affect epidemic outcomes.[19]

His research also extends into computational social science, including studies of online discourse and misinformation. He co-authored "Correction: Impact and dynamics of hate and counter speech online," published in EPJ Data Science in 2023 and cited 3 times, which is part of a broader research thread examining how hostile and counter speech spread and interact on social media platforms.[20] Related work, "Correction: The penumbra of open source: projects outside of centralized platforms are longer maintained, more academic and more collaborative," published in EPJ Data Science in 2022, examines the sustainability and collaborative dynamics of open source software projects.[21]

Additional research interests include the study of online group dynamics and detection of manipulated media. His 2022 paper "Distinguishing In-Groups and Onlookers by Language Use," presented at the Workshop on Computational Approaches to Subjectivity, Sentiment and Social Media Analysis, examines linguistic patterns that differentiate community insiders from external observers in online discourse.[22] His paper "Lifelikeness is in the eye of the beholder: demographics of deepfake detection and their impacts on online social networks," presented at LIFELIKE in 2022, examines how different demographic groups vary in their ability to detect deepfake media and the implications for social network dynamics.[23]

He has also contributed to the broader academic community through editorial work, including serving as an editor for the 2022 special issue introduction "Editorial: Introduction to the 2020 Conference on Artificial Life Special Issue," published in the journal Artificial Life.[24]

Across this body of work, Hebert-Dufresne's research demonstrates a consistent focus on applying network science and mathematical modeling to questions spanning public health, computational social science, and the philosophy of complex systems, with particular attention to how multiple contagion-like processes interact within populations and networks.[25]

Recognition

Hebert-Dufresne's research has been recognized through sustained federal funding from both the National Science Foundation and the National Institutes of Health, reflecting peer assessment of the scientific merit and public health relevance of his work.[26] His continued affiliation with the Santa Fe Institute, an institution known for its interdisciplinary approach to complexity science, further situates his work within an established network of complexity researchers.[27]

Publications

  • Hebert-Dufresne, L. et al. "One pathogen does not an epidemic make: A review of interacting contagions, diseases, beliefs, and stories." arXiv.org, 2025.
  • Hebert-Dufresne, L. "The path of complexity." npj Complexity, 2024.
  • Hebert-Dufresne, L. et al. "Biomedical open source software: Crucial packages and hidden heroes." PLoS Computational Biology, 2024.
  • Hebert-Dufresne, L. et al. "Temporal and Probabilistic Comparisons of Epidemic Interventions." Bulletin of Mathematical Biology, 2023.
  • Hebert-Dufresne, L. et al. "Correction: Impact and dynamics of hate and counter speech online." EPJ Data Science, 2023.
  • Hebert-Dufresne, L. et al. "The unintended consequences of inconsistent closure policies and mobility restrictions during epidemics." BMC Global and Public Health, 2023.
  • Hebert-Dufresne, L. "Editorial: Introduction to the 2020 Conference on Artificial Life Special Issue." Artificial Life, 2022.
  • Hebert-Dufresne, L. et al. "Distinguishing In-Groups and Onlookers by Language Use." Workshop on Computational Approaches to Subjectivity, Sentiment and Social Media Analysis, 2022.
  • Hebert-Dufresne, L. et al. "Correction: The penumbra of open source: projects outside of centralized platforms are longer maintained, more academic and more collaborative." EPJ Data Science, 2022.
  • Hebert-Dufresne, L. et al. "Lifelikeness is in the eye of the beholder: demographics of deepfake detection and their impacts on online social networks." LIFELIKE, 2022.
  1. ↑ University of Vermont, Department of Computer Science faculty directory.
  2. ↑ Semantic Scholar author profile, Laurent Hebert-Dufresne.
  3. ↑ Semantic Scholar author profile, Laurent Hebert-Dufresne, metrics accessed 2024.
  4. ↑ 4.0 4.1 Laurent Hebert-Dufresne, curriculum vitae, https://laurenthebertdufresne.github.io/file/LHD_CurriculumVitae.pdf
  5. ↑ University of Vermont Complex Systems Center, faculty listing.
  6. ↑ University of Vermont Department of Computer Science faculty page, Hebert-Dufresne.
  7. ↑ National Science Foundation award abstract, Network Comparison, a Cornerstone of the Foundations of Network Science, Santa Fe Institute, 2016.
  8. ↑ National Science Foundation award abstract, University of Vermont & State Agricultural College, 2018.
  9. ↑ National Science Foundation, Award Search database, Network Comparison, a Cornerstone of the Foundations of Network Science.
  10. ↑ National Science Foundation award abstract, Network Comparison, a Cornerstone of the Foundations of Network Science.
  11. ↑ National Institutes of Health, RePORTER database, Mathematical, Computational, and Predictive Modeling Core, University of Vermont & St Agric College.
  12. ↑ NIH RePORTER project abstract, Mathematical, Computational, and Predictive Modeling Core.
  13. ↑ Semantic Scholar publication list, Laurent Hebert-Dufresne.
  14. ↑ Semantic Scholar publication list, Laurent Hebert-Dufresne.
  15. ↑ Hebert-Dufresne, L. et al. "One pathogen does not an epidemic make: A review of interacting contagions, diseases, beliefs, and stories." arXiv.org, 2025.
  16. ↑ Hebert-Dufresne, L. "The path of complexity." npj Complexity, 2024.
  17. ↑ Hebert-Dufresne, L. et al. "Biomedical open source software: Crucial packages and hidden heroes." PLoS Computational Biology, 2024.
  18. ↑ Hebert-Dufresne, L. et al. "Temporal and Probabilistic Comparisons of Epidemic Interventions." Bulletin of Mathematical Biology, 2023.
  19. ↑ Hebert-Dufresne, L. et al. "The unintended consequences of inconsistent closure policies and mobility restrictions during epidemics." BMC Global and Public Health, 2023.
  20. ↑ Hebert-Dufresne, L. et al. "Correction: Impact and dynamics of hate and counter speech online." EPJ Data Science, 2023.
  21. ↑ Hebert-Dufresne, L. et al. "Correction: The penumbra of open source: projects outside of centralized platforms are longer maintained, more academic and more collaborative." EPJ Data Science, 2022.
  22. ↑ Hebert-Dufresne, L. et al. "Distinguishing In-Groups and Onlookers by Language Use." Workshop on Computational Approaches to Subjectivity, Sentiment and Social Media Analysis, 2022.
  23. ↑ Hebert-Dufresne, L. et al. "Lifelikeness is in the eye of the beholder: demographics of deepfake detection and their impacts on online social networks." LIFELIKE, 2022.
  24. ↑ Hebert-Dufresne, L. "Editorial: Introduction to the 2020 Conference on Artificial Life Special Issue." Artificial Life, 2022.
  25. ↑ Semantic Scholar publication list, Laurent Hebert-Dufresne.
  26. ↑ National Science Foundation Award Search database; NIH RePORTER database.
  27. ↑ Santa Fe Institute research affiliations.
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