Salma Mesmoudi.

113, rue Nationale

75013 Paris


Phone: +33 6 37 02 38 47

Professional info

Salma Mesmoudi, PhD, research engineer in Paris 1 Panthéon-Sorbone university MATRICE Project at Institute of System complexe since 2012. I received my PhD in Artificial intelligence from the UFR of arificial intelligence and bioinformatics in the École National de Sciences Appliquée de Tanger (ENSAT) in Morocco, on November 2005. I was a postdoctoral researcher at the « Institut National de rechercher en Informatique et Automatique (INRIA) » on 2008, the Laboratory of informatique at UPMC (LIP6) during 2009, the « Institut National de recherche Agronomiques (INRA) » on 2010, and the laboratory of biomedical imaging (LIB) at the Institute of health and medical research (Inserm 2011). I am a member of Complex System Socity. My research activity is related to the integration of the large multi-source and multi-scale data. 

Work experience

Research engineer Paris I Panthéon-Sorbone university

January 2013- Today

  • Scientific leader of the linkRbrain platform:  a web application for integration of brain's multi-scale knowledge

  • Scientific leader  of the biblioSynth platform: a web application for a visualization of the knowledge extracted by text mining from pubmed corpus.

  • Responsable scientifique de la plate forme biblioSynth: application web pour une visualisation des connaissances extraites par textmining à partir de corpus de pubmed.

  • Study of the behavior of visitors to the Caen memorial by analyzing and reconstructing their trajectories: eye tracking and motion sensors

Independent expert for European research and innovation Horizon 2020 European Commission

december 2015 – Today

Horizon 2020 is the eighth phase of the Framework Programs for Research and Technological Development funding programs created by the European Union in order to support and encourage research in the European Research Area.

Lecturer of Master EdTech at Paris VII

Septembre 2014 - Aujourd'hui

cours Master M1-M2: Participative and Citizen Sciences.

Open Science allows citizens to participate in the scientific research process in different possible ways: as observers, as funders, by identifying images or/and analysing data, or by providing data themselves. This allows for the democratisation of science, and it is also linked to stakeholders' engagement and public participation.

In this course we will introduce the basis of how we could making an open science from the conception of the project, how people could contribute to this project, the basis of open licence, the use of open file formats to exchange or diffuse knowledge, and finally, open used and produced data.

Post-doctoral fellow at Inserm

2010 - 2012


  • Subject: Treatment of large quantities of data in the field of functional imaging of the brain, genomics, and scientific bibliography.

  • Goals:

    • Design of data-mining and text-mining strategies for medical data

    • Design of new strategies for the processing of large masses of data

  • Results:

    • Linking of multimodal MRI images obtained by different methods (networks of functional connectivity, cognitive networks, anatomical networks) and genetic expression maps.

    • Proposition of a new functional model that integrates these different sets of results of brain imaging and genetics.

Post-doctoral fellow at Lip6 (DEcision team), CREA, INRA

​2009 - 2010

  • Subject: Robustness of agri-food process dynamics:

    • Analysis of the viability core and trajectories in the nucleus.

  • Goal:

    • Development of a robustness calculation software of a viability tube based on the geometrical calculation of the distances of all viable system states over the border.

    • Modeling the problem of the viability of an agri-food product as a multiobjective optimization problem

  • Results:

    • Geometric analysis of the viability core of the process of cheese finishing.

    • Modeling of an agro-food process as a multi-objective problem.

    • Design and development of data processing and optimization: evolutionary algorithms,and clustering.

    • Optimization of the agro-food process

Post-doctoral fellow at l'INRIA - CNRS

​2008 - 2009

  • Subject: Development of multi-objective meta-heuristics for solving docking problems

  • Goal:

    • Design of cooperative methods based on meta-heuristics.

    • Integration of the algorithms developed in the C++ ParadisEO software platform (

    • Experimentation through applications of problems of molecular modeling: docking and 3D structure prediction.

  • Results:

    • Design and integration of two meta-heuristics to the ParadisEO software: Variable Neighborhood Search (VNS) and Threshold Accepting (TA).

    • Design of hybrid method (VNS and evolutionary algorithm): application to the problem of molecular docking and prediction of the 3D structure of the proteins.

    • Participation in design and modeling of the multi-objective optimization module of ParadisEO platform.








Data mining 

text mining

multiobjective optimization

Complex systems

Multiscale integration

2010 - present

2010 - present

PhD. in Computer Science

Abdelmalek University

Essaadi, School of Applied Sciences at Tanger (ENSAT).

2010 - present

  • UFR: Artificial Intelligence and Bioinformatics, 

  • Title:  Modeling of memetic system for solving the travel salesman problem: application to the genome physical mapping. 


Conference Organisation

  • Local Organizer for BrainHack2013,  (october 23-26th, 2013) at CIEP Paris (

  • Co-organizer for SoData ! conference , (mars 14th, 2013-2014 at IGN Paris (

  • Organizational background of the International Workshop  The systematic and automated analysis of the Large functional brain databases of papers, (october 30th, 2012) at ICM, Paris. 

  • Co-Organizer of "La premiere journée thématique sur les méthodes de calcul GPGPU" (Febuary 10th) at ISCPIF.

  • Organizer of "From open data to multi-level cerebral dynamics" (September 14th 2015) at ISCP-PIF 

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