Dr. Jean-Daniel Fekete | Visualization | Best Researcher Award

Senior Research Scientist at National Institute for Research in Digital Science and Technology (INRIA), France.

Jean-Daniel Fekete is a Senior Research Scientist (Directeur de Recherche 1e Classe) and the Head of the Aviz Inria Team at Inria Saclay, France. He is also a faculty member at Université Paris-Saclay in the Computer Science Department. A pioneer in information visualization, visual analytics, and human-computer interaction, Fekete has made significant contributions to progressive data analysis, network visualization, and interactive systems. He has been an influential researcher and educator, with multiple high-impact publications and awards in visualization research.

Professional Profile:

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Education Background

1. Habilitation à diriger les recherches (Tenure) – University of Orsay Paris-Sud (2005)

• Thesis: “Nouvelle génération d’Interfaces Homme-Machine pour mieux agir et mieux comprendre” (Next-generation Human-Computer Interfaces for Better Understanding and Interaction)
• Jury included Joëlle Coutaz, Saul Greenberg, Ben Shneiderman, Michel Beaudouin-Lafon, among others.

2. Ph.D. in Computer Science – University of Paris-Sud (1996)

• Dissertation: “Un modèle multicouche pour la construction d’applications graphiques interactives” (A Multilayer Model for Building Interactive Graphical Applications)
• Research conducted at the Laboratoire de Recherche en Informatique (LRI).

3. DEA (Master’s) in Computer Science – University Paris-8 (1989)

Professional Development

Jean-Daniel Fekete has over 35 years of experience in research, academia, and industry. His career highlights include:

1. Senior Research Scientist (DR1), Aviz Project-Team, Inria Saclay (since 2013)

   • Leads a research group in visual analytics, network visualization, and human-computer interaction.

   • Developed groundbreaking progressive data analysis methods.

2. Senior Research Scientist (DR2), Aviz Project-Team, Inria Saclay (2006-2013)

3. Visiting Scholar

   • New York University – Polytechnic Institute (NYU-Poly) (Sabbatical, 2015)

   • Harvard University (Sabbatical, 2015)

   • Human-Computer Interaction Lab, University of Maryland (2001-2002)

4. Assistant Professor & Head of the Interactive Design and Modeling Group, Ecole des Mines de Nantes (1996-2001)

5. Principal Software Architect for “Tic Tac Toon”, a professional animation system, France (1989-1995)

6. Software Developer & Co-founder, C2V, a French startup in visualization (1987-1989)

7. Research Assistant

   • INRIA Rocquencourt (1985-1986) – Distributed Operating Systems

   • Centre Mondial de l’Informatique, Paris (1982-1986) – Medical Informatics for developing countries

Throughout his career, Fekete has developed high-impact visualization software, led funded research projects, supervised Ph.D. students, and actively contributed to professional societies like IEEE VIS, ACM SIGCHI, and Eurographics.

Research Focus

Jean-Daniel Fekete’s research focuses on:

1. Information Visualization & Visual Analytics

   • Techniques for exploring large, complex, and multidimensional data.

2. Progressive Data Analysis

   • Developing computational methods for scalable real-time data exploration.

3. Network & Graph Visualization

   • Methods for analyzing social networks, brain connectivity, and dynamic systems.

4. Human-Computer Interaction (HCI)

   • Designing interactive systems for improved user experience and decision-making.

5. Machine Learning & Explainable AI (XAI)

   • Enhancing interpretability of AI models through interactive visualization.

His contributions have had applications in healthcare, finance, cybersecurity, and smart cities.

Author Metrics:

Jean-Daniel Fekete has an extensive publication record, with over 200 peer-reviewed papers in top conferences and journals, including:

• IEEE Transactions on Visualization and Computer Graphics (TVCG)

• ACM Transactions on Computer-Human Interaction (TOCHI)

• IEEE InfoVis, IEEE VAST, IEEE VIS, ACM CHI, ACM UIST, EuroVis

Awards and Honors:

Publication Top Notes

1. Visual Analytics: Definition, Process, and Challenges

• Authors: D. Keim, G. Andrienko, J.-D. Fekete, C. Görg, J. Kohlhammer, G. Mélançon
• Source: Information Visualization: Human-Centered Issues and Perspectives, pp. 154-175
• Year: 2008
• Citations: 1805
• Summary: This paper defines visual analytics, outlines its process, and discusses key challenges in integrating analytical reasoning with interactive visualization.

2.  Nodetrix: A Hybrid Visualization of Social Networks

• Authors: N. Henry, J.-D. Fekete, M. J. McGuffin
• Source: IEEE Transactions on Visualization and Computer Graphics, 13(6), 1302-1309
• Year: 2007
• Citations: 791
• Summary: Introduces Nodetrix, a hybrid visualization technique combining node-link diagrams and adjacency matrices to improve the readability of complex social network structures.

3. Visual Analysis of Large Graphs: State‐of‐the‐Art and Future Research Challenges

• Authors: T. Von Landesberger, A. Kuijper, T. Schreck, J. Kohlhammer, J. J. van Wijk, J.-D. Fekete, et al.
• Source: Computer Graphics Forum, 30(6), 1719-1749
• Year: 2011
• Citations: 783
• Summary: Provides a comprehensive survey on graph visualization, discusses existing techniques, and highlights key challenges for handling large and dynamic graphs.

4. Bi-Scale Density-Plot Enhancement Based on Variance-Aware Filter

• Authors: H. Bao, X. Chen, K. Lu, C. W. Fu, J.-D. Fekete, Y. Wang
• Source: Computers & Graphics, 104180
• Year: 2025
• Citations: 2
• Summary: Introduces a bi-scale density-plot enhancement method using a variance-aware filter for improved data visualization in large-scale applications.

5. Middleware for Online Exploration of Big Data

• Authors: F. Bugiotti, B. Groz, J.-D. Fekete
• Year: 2024
• Summary: Discusses middleware solutions enabling efficient and interactive exploration of large datasets in big data analytics environments.

Conclusion