CIMPA School 2027

Description of project

The school will focus on the progression from classical statistical inference to modern learning methods, highlighting their interplay and applications. The objective is to provide participants with a comprehensive understanding of the theoretical foundations of probability and statistics, their extension through stochastic modeling, and their role in contemporary statistical learning approaches.

The first part of the school will revisit the essential concepts of statistical inference, including estimation, hypothesis testing, and regression analysis, while emphasizing their limitations and the need for more flexible approaches. Building on this, the second part will introduce stochastic modeling as a bridge toward more complex data-driven problems, with a focus on random processes, stochastic calculus, and their applications. The final part will cover learning methods, ranging from supervised and unsupervised techniques to more advanced approaches such as ensemble models and neural networks. The emphasis will be on how these methods extend classical inference, enabling robust data analysis and predictive modeling in various applied domains, including population dynamics, finance, insurance, and risk management. Through lectures, tutorials, and practical sessions, participants will: acquire solid knowledge of the principles of statistical inference and stochastic modeling, develop practical skills in statistical learning methods and their implementation, apply theory to real-world problems through case studies and computational exercises, and build an international and regional research network.

By combining inference, modeling, and learning, this CIMPA School will equip participants with the conceptual tools and applied techniques needed to tackle modern challenges in data analysis and applied probability.

 

Local organizer:
Mintodê Nicodème ATCHADE
National University of Sciences, Technologies,
Engineering, and Mathematics (UNSTIM)
Benin
nickpowerabc@gmail.com
nicodemeatchade@unstim.bj

 

External organizer:
Christian Paroissin
Université de Pau et des Pays de l'Adour (UPPA)
France
christian.paroissin@univ-pau.fr