Samuel Thiriot

Monday 14 November 2016
English français

I received my Ph.D. degree in Computer Sciences from the french Université Pierre et Marie Curie (University of Paris 6) in 2009. I’m currently holding a post-doctoral position at the Institute of Research in Informatics of Toulouse IRIT funded by the RTRA foundation. I teach computer sciences for social sciences in the Université Toulouse 1 Capitole. Please refer to my resume (...forthcoming !) or my publications for more details.

Research activities

My research interests tackle three interdependent axes: agent-based modelling of social phenomena, social networks and ambient intelligence.

Agent-based modeling of social dynamics

Agent-based modeling is a modeling approach in which the social metaphor of multi-agent systems is applied to the study of collective dynamics. In the case of social phenomena, an agent-based model includes an artificial population of individuals (the agents) interacting in an environment. By using computational simulation, such a model enables the study of the (possibly complex) collective dynamics emerging from these local interactions and behaviors.

During my Ph.D. [7], I applied agent-based modeling to the diffusion of innovations (i.e. the communication of new products, practices or ideas) within a population, including the word-of-mouth process that underlies this social process [5]. I proposed to represent adopters’ beliefs as associative networks [3,4], thus improving the realism and usability of the model.

I’m nowadays studying the impact of social and legal norms on a socio-environmental environment. These researches are developed in the frame of the MAELIA pluridisciplinary project. These researches are currently focused on the use of water during scarcity periods in the Adour-Garonne watershed [9,11].

Social networks for agent-based simulation

Social network are used in social simulation to represent the structure of interactions within the population of agents. The properties of these networks are known to have a dramatic impact on the simulation results; as a consequence, I’m studying the criteria for network choice [12], along with new methods to generate more realistic interaction networks by using field observations [10,6].

Ambient Intelligence

The promise of Ambient Intelligence (AmI) is to organize the numerous devices present in the environment (ubiquitous computing) in order to enhance users’ well-being. An ambient system may be analyzed as a multi-agent system that is open, heterogeneous and collaborative. This system is built such it satisfies users’ needs and ensures the security of the environment. I’m working on communication protocols inspired by social processes [7] in order to solve several realistic scenarios.

Other activities

  • Founding president of the @res-ear.ch non-profit organization, which offers permanent email forwarding for researchers.
  • Co-organizer of the MARAMI’10 workshop, co-organized with IRIT and IMT (MARAMI stands for Models and Use of Networks: Mathematical and Computer sciences Approches, in french "Modèles et Applications des Réseaux: Approches Mathématiques et Informatiques)
  • Co-organizer of SNAMAS 2011

(c) Samuel Thiriot 2012-2016
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