2027

Flavors of Representation Theory (FoRT) is a two-week workshop focused on contemporary developments in representation theory and its interactions with algebra, geometry, combinatorics, topology, and mathematical physics. The programme presents a range of themes including infinite-dimensional Lie theory, homological and categorical methods, cluster structures, combinatorial algebras, knot-theoretic connections, and representations of groups over finite and p-adic fields.

The school focuses on the progression from classical statistical inference to modern learning methods, emphasizing their interplay and applications. It aims to provide participants with a solid understanding of probability and statistics, their extension through stochastic modeling, and their role in contemporary statistical learning. The first part revisits key concepts of inference, including estimation, hypothesis testing, and regression, highlighting their limitations.

Functional Data Analysis (FDA) has become an important field in statistics, facilitating the study of data in the shape of functions, curves, and surfaces. With applications spanning biomedicine, neuroscience, climate science, and engineering, FDA offers robust methods for modeling high dimensional, spatial-temporal, and intricately structured data. While FDA is a widely recognized research field in the Global North, its presence is still limited across Africa.

The CIMPA School on Mathematical Modeling and Machine Learning for Biomedicine and Public Health will take place from May 31 to June 9, 2027, at Tribhuvan University in Kathmandu, Nepal. This intensive 10-day program offers participants a unique opportunity to bridge theoretical research with practical applications through expert-led lectures and hands-on computer labs. Attendees will master advanced topics, including between-host and within-host dynamics, stochastic modeling, and the integration of machine learning with mechanistic systems like PINNs.

The school will present three active domains which are recent developments with origin in symbolic dynamics: progresses in the theory of tilings, questions of diophantine approximation and proofs of transcendance for some number with explicit expansions in a given base, and generalisations of the classical notion of substitution; the unifying theme will be to show how symbolic dynamics can be applied to obtain results in very different contexts.

Cette école se situe à l'interface des mathématiques fondamentales et de l'informatique théorique. Elle explore comment les outils avancés d'analyse, d'algèbre, de combinatoire et de probabilités nourrissent les développements modernes en informatique, notamment en cryptographie, vérification formelle, apprentissage automatique et algorithmique. Les participant·es découvriront les fondements mathématiques qui sous-tendent ces domaines clés.

Arithmetic geometry lies in the intersection of number theory and algebraic geometry. It involves studying geometric objects such as curves or varieties through an arithmetic lens, e.g. via their rational points. As a research area, it dates back to classical questions such as those in Diophantine geometry, and yet continues to develop rapidly in the modern mathematical context. It is wide in scope, using a variety of techniques from algebraic geometry, algebraic and analytic number theory, and computational mathematics.

El programa Modern Techniques in Analysis and Differential Geometry integra dos áreas centrales de las matemáticas modernas: el análisis matemático y la geometría diferencial, con una progresión académica que va desde nivel avanzado de licenciatura hasta posgrado. Incluye seis cursos organizados en tres niveles. En análisis, los estudiantes avanzan desde modelos aplicados en epidemiología hasta ecuaciones diferenciales holomorfas, pasando por métodos analíticos y numéricos en dinámica de fluidos geofísicos.

Le but de l'atelier collaboratif est de permettre un travail de recherche, dans différents thèmes d'actualité en géométrie, théorie des nombres ou algèbre, sous la direction d'un binôme composé à chaque fois d'une personne d'Europe et d'une personne d'Afrique. Chaque sujet de recherche comportera à la fois une étude théorique, des exemples, des calculs et des applications. Des séances d'introduction, d'étape et de conclusion permettront d'informer l'ensemble participant.es du travail des autres groupes.

Cette école vise à initier les doctorants et jeunes chercheurs aux méthodes modernes de modélisation mathématique et aux outils d’intelligence artificielle (IA), appliqués à des problématiques concrètes en santé publique, épidémiologie, écologie, ou environnement. Les participants découvriront des techniques théoriques et numériques leur permettant de formaliser, simuler, analyser et interpréter des systèmes complexes, notamment ceux modélisant la propagation de maladies, l’évolution d’écosystèmes, ou l’impact de politiques de santé/environnement.