South Africa

The aim of this CIMPA school will be to familiarise graduate students and young researchers with the field of  enumerative and analytic combinatorics,  and to show its many connections to other areas,  especially computer science.  The courses  range from introductory to  more advanced levels.

The research school will provide a useful background to understand several of the very active research subjects in the wide area of functional analysis. This includes Riesz spaces and Stochastics processes, function theory, differential operators, operator theory on various and natural Banach spaces, some notions of geometry of Banach spaces, semigroup theory and its links with applications, without omitting an introduction to harmonic analysis.

The aim of this CIMPA school will be to familiarise graduate students and young researchers with the field of  enumerative and analytic combinatorics,  and to show its many connections to other areas,  especially computer science.  The courses  range from introductory to  more advanced levels.

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.

Recent years have witnessed the emergence of powerful semantic tools for non-classical logics. These semantic methods draw from web of mathematical formalisms at the intersection of ordered and universal algebra, topology, and category theory, and together provide a flexible and unifying framework for the study of logic across a host of domains. LIACT serves as a broad introduction to this dynamic and quickly growing area of modern mathematical research, and places particular emphasis on this area's deep interactions with/and applications to computer science.

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.

A blockchain is a digital list of data records, comprised by blocks which are organized in chronological order and are linked and secured by cryptographic proofs.

It started to secure digital documents from data tampering, and quickly lead to the creation of Bitcoin, the first decentralized electronic cash system, or cryptocurrency.

Mathematical and statistical modeling in oncology is a multidisciplinary field that applies mathematical and statistical techniques to understand, describe, and predict various aspects of cancer biology, epidemiology, and treatment. It plays a crucial role in advancing our understanding of cancer, optimizing treatment strategies, and informing healthcare decision-making.

The aim of this CIMPA school will be to familiarise graduate students and young researchers with the field of enumerative and analytic combinatorics, and to show its many connections to other areas, especially computer science.