Maître de Conférences

bourqui [at]
LaBRI, Université de Bordeaux
351, cours de la Libération
F-33405 Talence cedex
Tel.: +33 5 4000 3530
About me

Since 1st 2009, I am an Associate Professor in the Computer Science Department of the IUT ("Technical School"), University of Bordeaux (Talence), France. I am also head of the BKB ("Bench to Knowledge and Beyond") team of LaBRI.

From 1st October 2008 to 31st August 2009, I was post-doctoral researcher in computer science with the VIS team of the Eindhoven University of Technology, Netherlands. My collaborators there were J. J. van Wijk and M. A. Westenberg.

September 2005 to October 2008, Phd in Computer Science with LaBRI laboratory, University of Bordeaux:

"Graph decomposition and Visualization: Applications to Biological Data" (in French)
supervised by David Auber and Maylis Delest.

Research Activity

The development of data acquisition techniques makes possible the generation more and more data. The size and complexity of this data raises a new problem: do traditional data analysis tools (e.g. diagrams, spreadsheets, etc.) allow to explore them efficiently? It seems obvious that the analysis of a list of several thousand (or even millions or billions) of lines requires a significant effort for experts. This constant increase therefore makes crucial the design of data exploration and analysis tools that allow their exploitation. This is even the more true in the era of Big Data, where the size of data far exceeds the capabilities of conventional computers. The objective of my research work is therefore the development of such tools. In order to allow the visual exploration of complex and/or massive data, my work focuses on the definition of graph drawing algorithms and the definition of data summary visualizations, also called abstract visualizations.

The improvement of computing power as well as the availability of large data sets, especially in distributed infrastructures, have allowed the development of supervised learning methods. However, these methods, and in particular deep neural networks, are difficult to explain. This makes them currently unusable in certain application domains such as health and security. These networks offer particularly interesting case studies due to their size and complexity. The current direction of my research is not only oriented towards visualization for supervised learning in order to explain the predictions, improve their performance or reduce their size in order to reduce the necessary computing resources (energy cost, implementation in connected objects), but also towards the use of these methods for the automatic evaluation of visualization techniques.


On going project:

  • INVOLVD Project (Interactive constraint elicitation for unsupervised and semi-supervised data mining), ANR PRC 2020-2024, work package co-leader

Previous projects:

  • MIAM Project (Maladies, Interactions Aliment Médicaments), ANR PRCE 2017-2020, funding: 175K€
  • e-ATM Project, ANR MRSEI 2016-2017, local funding:22K€
  • DIMMER Project (Détection et surveillance des Mésusages de Médicaments dans les for a de santé et les Réseaux sociaux), PEPS conjoint IdEx Bordeaux / CNRS 2016-2017, local funding: 21K€
  • MVDE Project (Médiation et valorisation des données ouvertes et des données de recherche pour l'éducation), PEPS conjoint IdEx Bordeaux / CNRS 2016-2017
  • EVA TSN Project (Evaluation de la mise en oeuvre et des résultats du programme Territoire de Soins Numérique dans les cinq territoires pilotes) PREPS (Programme de Recherche sur la Performance su Système de soins) 2014-2018, local funding: 1.4M€
  • MycoRNA Project, PEPS conjoint IdEx Bordeaux / CNRS 2013-2014, funding: 21K€
  • R-VIZ Project, Appel à Projet de l'Université Bordeaux 1 2013-2014, 28K€
  • Speed Data Project, Programme d' Investissements d'Avenir, appel à projets cloud computing nº3 Big data 2013-2017, local funding: 600K€ (funding: 1.2M€), Project scientific leader
  • REQUEST Project, Programme d'Investissements d'Avenir, appel à projets cloud computing nº3 Big data 2013-2016. local funding: 550 K€
  • EVIDEN Project (Exploration and Visualization of Dynamic Relational ANR JCJC 2010-2014, funding: 243K€

Students supervision

On going supervision:

Former students:

  • ClĂ©ment Thomas, MSc in Bioinformatics (feb-july 2023), University of Bordeaux, co-supervised (50%) with Loann Giovannangeli.
  • Gaëlle Richer, Phd (2016-2019), co-supervised (50%) with David Auber, current position: Postdoc in AVIZ team, Inria and University of Paris-Saclay, France.
  • Quoc Truong Le, MSc in Computer Science (april-sept. 2019), PUF Ho-Chi-Minh-Ville, Vietnam, co-suypervised (50%) with Romain Giot.
  • Alcuyet Gaizka, Engineer (march-august 2018), ISIMA Clermont-Ferrand, co-suypervised (50%) with Romain Giot.
  • Joris Sansen, Phd (2013-2017), co-supervised (80%) with David Auber, current position: Associate professor at ENSTBB-Bordeaux INP, France.
  • François Queyroi, Phd (2010-2013), co-supervised (30%) with Maylis Delest, current position: Researcher at CNRS, LS2N, University of Nantes, France.
  • Antoine Lambert, Phd (2009-2012), co-supervised (20%) with David Auber and Guy Melançon, current position: Senior Software Engineer at Software Heritage, Paris, France.
  • Nguyen Huy, MSc in Computer Science (june-dec. 2011), PUF Ho-Chi-Minh-Ville, Vietnam, co-suypervised (50%) with Nicolas Hanusse.

Research administration
Teaching administration
Département Informatique, IUT de Bordeaux
  • Initiation à la programmation, 1ère année (S1), M1102-M1103 (accès restreint).
  • Initiation à la programmation orientée objet, 1ère année (S2), M2103 (accès restreint).
  • Graphes et Langages (partie Graphes), 1ère année (S2), M2201 (accès restreint).
  • Programmation C, 2ème année (S3), M3103 et M3101 (accès restreint).
  • Algorithmique avancèe, 2ème année (S3), M1102-M1103 (accès restreint).
  • Projet Tuteuré, 2ème année (S4), M4106 (accès restreint).
Master 2 Bio-informatique, Université de Bordeaux
  • Visualisation de données biologiques, 2ème année (S9), module "Données: De l'Entrepôt à l'Analyse".
3ème année, parcours IA, ENSC/ENSEIRB-MATMECA
  • Visualisation d'information, 2ème année (S9), module "Analyse de données et visualisation".
Software & prototypes
PIVERT: a suite of prototypes for interpreting Deep Neural Netowrks
PIVERT website can be found here.
rNAV: a visualization tool for bacterial sRNA-mediated regulatory networks mining
rNAV website can be found here.
Systrip: a visual environment for the investigation of time-series data in the context of metabolic networks
Systrip website can be found here.
MetaViz: Visualization software for metabolic network
MetaViz website can be found here.
MotusVis: Software for visual comparison of metabolic networks
A demo can be found here.
Tulip: Framework dedicated to the analysis and visualization of relational data
Tulip webstite can be found here.