PeopleofSuperintelligence

Researcher

Jean‐Loup Guillaume

Also known as Jean-Loup Guillaume

Jean-Loup Guillaume is a computer scientist who helped create the Louvain method, a fast community-detection algorithm for large networks that serves tasks such as friend and purchase recommendation. He defended a PhD on complex networks under Matthieu Latapy in 2004 and codeveloped the method in 2007 as a postdoctoral fellow at Université Catholique de Louvain, with Vincent Blondel, Renaud Lambiotte and Etienne Lefebvre. After joining Université Pierre et Marie Curie as an associate professor in 2008, he coordinated the ANR project CODDDE, which began in 2013, and became a professor at La Rochelle Université in 2014. In 2023, he coauthored a 15-year review of the Louvain method with Blondel and Lambiotte. He is a full professor at La Rochelle Université in the L3i laboratory, where his recent papers cover overlapping and multilayer communities and topic modeling.

Now at
La Rochelle Université
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Timeline

  1. 2004

    PhD on complex networks

    He defends his thesis 'Statistical analysis and modeling of complex networks' in December 2004. He works at LIAFA, in the Algorithm and Combinatorics group, under the supervision of Matthieu Latapy.

  2. 2007–2008

    The Louvain method

    As a postdoctoral fellow in the INMA research group 'Large Graphs and Networks' at Université Catholique de Louvain, he works with Vincent Blondel and codevelops the Louvain method in 2007. The 2008 paper 'Fast unfolding of communities in large networks', written with Blondel, Renaud Lambiotte and Etienne Lefebvre, appears in J. Stat. Mech. and tests the method on a Belgian mobile phone network of 2.6 million customers and a web graph of 118 million nodes. The method serves to understand network structure and to recommend friends, contacts and purchases.

  3. 2008–2012

    Associate professor at LIP6

    He becomes an associate professor (maître de conférences) at Université Pierre et Marie Curie in 2008, in the Complex Networks team of the LIP6 laboratory. In November 2012, he defends his Habilitation à Diriger les Recherches on community detection in complex networks.

  4. December 2013

    Coordinating the CODDDE project

    In December 2013, he starts coordinating CODDDE (COmmunity Dynamics, Diffusion and Detection of events), a French National Research Agency project funded with 366,354 euros. Its partners are the Complex Networks team of LIP6 at Université Pierre et Marie Curie, the LIP team at ENS Lyon and the company Linkfluence. The project studies how real-world networks evolve, how information spreads on them and how unexpected changes can be detected.

  5. October 2014

    Professor at La Rochelle

    In October 2014, he joins La Rochelle Université as a professor in the L3i laboratory (Laboratoire Informatique, Image et Interaction), in the Models and Knowledge team.

  6. 2023

    A 15-year review of Louvain

    By August 2023, the Louvain method counts more than 20,000 citations. In November 2023, he submits a review of the method with Vincent Blondel and Renaud Lambiotte, giving an overview of its generalizations and modifications and surveying the quality functions, beyond modularity, for which it has been implemented.

  7. 2025–2026

    Overlapping and multilayer communities

    His papers in 2025 and 2026 include 'Dynamic and Overlapping Community Detection in Link Streams through Formal Concept Analysis', written with Christophe Demko, Karell Bertet and Martin Waffo Kemgne. Others are 'Is Word2Vec Dead for Topic Modeling?', a hospitality opinion-mining study with Marc-Alexis Azaïs and Mickael Coustaty, and 'Multilayer Louvain', a modularity-based community detection algorithm for multilayer networks written with Bivas Mitra and colleagues.

  8. As of October 2026

    Full professor at L3i

    He is a full professor at La Rochelle Université, in the Models and Knowledge team of the L3i laboratory, known for work on complex networks and community detection. By 2024, he has supervised 12 theses and takes part in the ANR projects MITIK, on mobility and contact traces from passive measurements, and Smart-FCA, on Formal Concept Analysis for complex data.

Career

  1. Since 2014La Rochelle UniversitéFull Professor
  2. 2008–2012Sorbonne UniversityAssociate Professor
  3. 2007–2008UCLouvainPostdoctoral Fellow

Education

  1. 2004LIAFAPhD

From the biography.

  1. The Massachusetts Institute of Technology trained or employed 44 of the 187 AI major-prize winners, more than any other universityIncludes Sorbonne University. The Massachusetts Institute of Technology trained or employed 44 of the 187 AI major-prize winners, more than any other university. We compare doctorate and 5+ year employment links, career timing and current workplaces for 187 major-prize and 1,111 best-paper winners.
  2. More people shaping AI studied at Massachusetts Institute of Technology than at any other institutionIncludes Sorbonne University. We estimate where the people shaping AI studied and where their careers led. Massachusetts Institute of Technology leads with 467 former students, including 291 recorded doctorates.
  3. The company share of AI researchers’ top papers was 31% in 2020–2024 and 8% in 1970–1974Includes Sorbonne University. We estimate where the people shaping AI worked when their most-cited papers appeared: the company share was 31% in 2020–2024 and 8% in 1970–1974, and Google led all organizations in 2020–2024.
  4. Google has the highest combined h-index among AI organizationsIncludes Sorbonne University. We estimate that Google holds the highest combined h-index at 8,016, while universities account for 73% of the deduplicated total across AI organizations.

Colleagues

People named in this biography, and people with dated positions at the same organization in the same years.

Sources and credits

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  1. Jean-Loup Guillaume website perso.lip6.fr. Checked 21 October 2026.
  2. Jean-Loup Guillaume - La Rochelle Université univ-larochelle.fr. Checked 21 October 2026.
  3. [0803.0476] Fast unfolding of communities in large networks arxiv.org. Checked 21 October 2026.
  4. Programme_2024 – JIDAP L3i jidape.univ-lr.fr. Checked 21 October 2026.
  5. Evolving communities, diffusion and events detection | ANR anr.fr. Checked 21 October 2026.
  6. [2311.06047] Fast unfolding of communities in large networks: 15 years later arxiv.org. Checked 21 October 2026.
  7. Publications – Page 1 sur 4 – L3i l3i.univ-larochelle.fr. Checked 21 October 2026.