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Hi, welcome to my personnal webpage. Enjoy your visit and please feel free to contact me at antoinebrias[@]gmail.com with any remark. You can also contact me on ResearchGate or Twitter.

Last year, I was a research engineer at the University of Corsica, where I had to analyze Dentex dentex stock data to provide an accurate state of the population around Corsica island. Several methods were compared to provide robust results.

From 2020 to 2022, I held a post-doctoral position at the University Clermont-Auvergne (UCA) under the supervision of Anne Bonis and Jean-Baptiste Pichancourt. We have built up a framework for the viability and adaptation of social-ecological systems such as hedgerow networks in agro-ecological landscapes.

I was previously a postdoc scholar at the University of California Santa Cruz (UCSC), under the supervision of Dr. Steve Munch. The goal of this project is to build harvesting policies for multi-species fisheries, based on model-free forecasting methods and reinforcement learning.

I finished my PhD in 2016 at Irstea-LISC under the direction of  Dr. Jean-Denis Mathias and Dr. Guillaume Deffuant. My PhD thesis aimed to hit back the curse of dimensionality in the computation of the viability kernel by using GPU parallelizing and reliability theory. This work was illustrated with study-cases of eutrophication and fisheries management.

My first research experience was an internship with Prof. René Ferland at the Université du Québec à Montréal in 2010, where I developed a genetic algorithm for mathematical optimization and a statistical tool computing mutual information of random variables. 

My research interests evolve around the modeling of complex systems and particularly environmental systems. I am interested in providing tools in decision making processes to manage systems which can be impacted by extreme events or environmental changes.

To this end, I am interested in the creation of algorithms and the use of high performance computing methods, such as parallelization, to assess a large number of problems. Finally, I am looking to continue the exploration of optimization methods and model calibration.