2027

The VI Latin American School on Algebraic Geometry will take place at Universidad de Antioquia, Colombia from June 21st to July 2nd, 2027. This school aims to bring together graduate students, postdoctoral researchers, and young mathematicians from Latin America and beyond for an intensive program centered on some of the most active topics in contemporary Algebraic Geometry. The VI Latin American School on Algebraic Geometry (ELGA) will be held at Universidad de Antioquia, Colombia, from June 21 to July 2, 2027.

This school focuses on modern statistical and data science methods to analyze and understand diseases. Topics include the identification of risk factors for a disease, its prevalence and incidence, statistical analysis of historical data, and prediction of its future spread. Organized by the Institute of Applied Statistics of the University of Burundi, this CIMPA School provides both theoretical foundations and practical applications of statistical techniques.

The main theme of this CIMPA School is Topological Data Analysis (TDA), an emerging field at the intersection of topology and data science that uses tools from Algebraic Topology to understand the “shape” of data. This school will provide participants with both foundational and advanced topics in TDA, along with an introduction to its integration with Machine learning techniques. The program is designed to support participants from diverse backgrounds through a structured sequence of introductory and advanced courses.

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.