OFFRE DE THESE OUVERTE : dans le cadre du projet Fluence, nous recrutons un doctorant (informatique ou sciences cognitives) pour 3 ans, à partir d’Octobre 2017. Sujet : la modélisation bayésienne de la lecture. Tous les détails dans le descriptif de l’offre : Fluence_PhD_FR.pdf.
OPEN PhD POSITION: as part of the Fluence project, we are looking for a student (computer science or cognitive science) for a PhD position, for 3 years, starting October, 2017. Topic: Bayesian modeling of reading. All details are found in the position description: Fluence_PhD_ENG.pdf.
Since 2005, I hold a full time research position at CNRS (French National Center for Scientific Research), and I work at the LPNC, the Psychology and NeuroCognition Laboratory, in Grenoble. In 2015, I have defended my HDR (Habilitation à Diriger des Recherches) in Computer Science (at the Ecole Doctorale “Mathématiques, Sciences et Technologies de l’Information, Informatique”).
My research concerns probabilistic modeling of sensorimotor systems. I am interested both in natural and artificial sensorimotor systems; in other words, my research is multidisciplinary, at the crossroads between mathematics and computer science, on the one hand, and cognitive science and experimental psychology, on the other hand.
In this context, I use Bayesian Programming as a modeling framework. This means defining cognitive models as probability distributions, which can be structured in an arbitrarily complex manner. Therefore, contrary to the current trend of Bayesian modeling as “optimal modeling”, I define Bayesian models at the algorithmic level of Marr’s hierarchy. The resulting “Bayesian algorithmic models” are then mathematically manipulated to predict function, thanks to Bayesian inference.
The main research topic I am interested in, in the context of Bayesian algorithmic cognitive modeling, is the interaction between perception and action processes. I work on three main objects of study:
- Bayesian modeling of speech perception and production;
- Bayesian modeling of reading and writing;
- Bayesian modeling of navigation (previously, no current research on this topic).
I am also interested in theoretical aspects of Bayesian Programming:
- studying the modeling-experiment loop in Cognitive Science;
- using probabilistic models to measure user performance.
If you wish to know more, you can find on this website more information: on the research page, I quickly describe some aspects of these 5 research topics, or you can browse my publication list, where relevant papers are accessible, or take a look at lecture slides and accompanying material (from the introductory lectures I give at the masters’ and PhD levels).
You can also always shoot me an e-mail for more information, or if you are interested in potential collaboration or internship. My email address is julien dot diard @ univ dash grenoble dash alpes dot fr. Comments about this website are also welcome! 🙂