2022

The summer school aims to gather young researchers and to give a motivating goal along which the participants will be able to aggregate new knowledge. The research topics include function field arithmetic, algebraic curves over finite fields, complex multiplication, boolean functions, finite geometry, and combinatorics. The school will be mostly structured into working sessions in small groups under the direction of at least one lecturer. Before the beginning of the school, the lecturers will propose open problems together with pre-request material (books/papers).

The University of Dhaka was established in 1921. Academic activities started on 1 July 1921, with three faculties: Arts, Science, and Law and 12 Departments including Mathematics. Historically, this University was in a leading position to establish "Bangla" as mother language in 1952 and played a vital role in 1971 for the independence of Bangladesh.

L’Ecole CIMPA “Algèbre, Arithmétique et Application” vise à offrir des sessions intensives à de jeunes chercheurs sur des domaines centraux des recherches actuelles en mathématiques fondamentales et appliquées. Nous avons sélectionné 4 cours : Introduction aux groupes algébriques ; Théorie analytique des nombres et approximation diophantienne ; Géométrie des courbes elliptiques ; Méthodes géométriques en théorie de l’information. Ces cours seront donnés par des chercheurs reconnus de leur domaine.

The school aims to introduce graduate students and young researchers to the recent connections between p-adic analysis (understood in a large sense) with mathematical physics and computer science. The courses will be focused on active research areas. The tentative list of courses include: (1) introduction to p-adic analysis; (2) introduction to local zeta functions; (3) p-adic models in quantum physics; (4) the p-adic theory of automata; (5) p-adic electrostatics; (6)  Strings amplitudes, local zeta functions, and log-Coulomb gases.

L’Ecole CIMPA sur la Géométrie et applications, Brazzaville 2020, a pour objectif de montrer aux étudiants des niveaux 2ème année de master, aux doctorants et aux jeunes chercheurs les différents types de Géométrie et la richesse des sujets développables. Le lien qui existe entre ces géométries et différentes branches des mathématiques (algèbre, analyse, informatique…), de la physique et d’autres sciences seront établis. Des applications seront formulées à travers des séances de travaux dirigés et pratiques. Quelques travaux des jeunes chercheurs seront également présentés.

Geometric group theory is a relatively new line of research on its own, inspired by pioneering works of M. Dehn, G.D. Mostow and M. Gromov. It is mainly devoted to the study of countable groups by exploring connections between algebraic properties of such groups and geometric properties of spaces on which these groups act, such as the deck transformation group of a Riemannian manifold. Geometric group theory is a very broad area, and this program aims at introducing young students to different aspects of the theory.

The school aims to introduce graduate students and young researchers to probabilistic and statistical models, including deterministic models focused on applications in environment and epidemiology. It is also aimed at non-specialist practitioners wishing to connect their research to the field of random modeling. The participants will be provided with an introduction to basic material and necessary background before proceeding with the more advanced topics. Beside lectures, we are also planning sessions devoted to solving exercices and computers experiments.

The project is to give backgrounds in rings, modules, and category and show applications in coding and modern computer Algebra. 

Langue officielle de l'école : anglais

La science des données et l'optimisation stochastique sont deux disciplines tout à fait complémentaires qui sont en plein essor aussi bien dans le monde universitaire que dans le secteur privé ou public. Les thèmes abordés dans cette école sont les suivants :

  - Méthode à noyaux et applications en sciences des données.

  - Statistique mathématique pour la science des données.

  - Modélisation aléatoire et simulations numériques.

  - Processus contrôlés markoviens et métaheuristiques.

The School aims to introduce students to the mathematical and statistical underpinnings of some of the latest Data Science methods that seek to address the challenge of Big Data analysis. There will be an emphasis on matricial methods both in modelling and in numerical computations. The topics covered will include Randomized Numerical Linear Algebra, Deep Generative Models, Bayesian Nonparametric Models and their Asymptotic Properties, Modern Graphical Models and High- Dimensional Statistics Based on Random Matrix Theory.