Dr. Eric PARENT Ph.D., born September 1957
UMR AgroParisTech/INRA 518
Team MORSE
French National Institute for Rural Engineering,Water and Forest Management
19, av du Maine 75732 Paris Cédex 15 FRANCE
Tel : +33 (0)1 45 49 89 28 or 44 08 18 88
fax : +33 (0)1 45 49 88 27
Research interests
- main field
Bayesian theory and applications, with special emphasis in environmental systems modeling.
Systems analysis and risk management in environmental resources. Decision making within a stochastic framework.
Bayesian design optimization via particle methods. Hierarchical and dynamic modelling in biometry and ecotoxicology. Peak over Threshold modelling for risk analysis of extreme events. Dynamic models and Bayesian detection of change point in hydro and environmental series. Hierarchical Bayesian Models for spatial data. Probabilistic forecasting with ensembles.
Who am I?
I work as a Professor in applied statistics and probabilistic modeling for environmental engineering. My research group belongs to the French National Institute for Rural Engineering, Water and Forest Management, an academic institution from the Ministry of Agriculture (Engref). The laboratory enrols PhD students and postgraduate engineers trained to work at the intersection between statistics, decision-making theory and environmental engineering. I co-authored three books (in French) , one on Bayesian statistics for environmental engineering, the second on theoretical and algorithmic aspects of Bayesian theory and the third one depicts various cases with real data from various domains of applications. My recent book in English is a tutorial to implementHierarchical Bayesian Modeling for Ecological data. My broader interests include “ Bayesian Statistics at work”, especially in case studies from various fields while working with my PhD students, under contract with industrial companies or public institutions. Some of our research interests can be found here . We organize regular bi-annual meetings at Rochebrune with my former PhD’s and some colleagues.
Teaching
- PhD. level, (24 hrs) Hierarchical Bayesian Modeling using OpenBugs.
- Msc. level, (48 hrs) Markov Chains for model elaboration and statistical inference : a mathematical approach to risk analysis. (48 hrs)
- Msc. level, (8 hrs). Introduction to Geostatistics for precision agronomical engineering .
Publications (here)