Nepal

<div class="tex2jax_process">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.

The objective of the school is to provide introductory training in Number Theory and Cryptography to graduate students and young researchers from Nepal and other countries in the same area.

We would like to adress the school to «pure mathematicians» not necessarily with a backgound in computing. Mathematicians from Nepal and neighboring countries need to develop activities in this direction.

The objective of our school is to propose courses from basic to advance level in Dynamical Systems, specially in Complex Dynamics and Ergodic Theory, to young mathematicians (from graduate level students to researchers) of Nepal and neighbouring countries.

This will be a school on dynamical systems in a rather wide sense, including background results on invariant manifolds and symplectic geometry (Chaperon), weak Kolmogorov-Arnold-Moser (KAM) theory and Arnold diffusion (Cheng, Seara), weak solutions of Hamilton-Jacobi evolution equations (Cheng, Wei), small denominators and KAM theory (Eliasson, Kuksin), partial differential equations (Cheng, Eliasson, Wei, Kuksin) and ergodic theory (Cheng, Luzzatto). Complex dynamics will be represented by a mini-course and a talk by Anna Miriam Benini (Rome).

The primary objective of this summer school is to provide an opportunity for mathematicians and biologists in Nepal and neighboring countries to explore mathematical skills that can be applied to address issues of real-life biological systems. The summer school aims to introduce students, junior faculty members, and young researchers to the important theories and appli- cations of Mathematical Biology.

The summer school aims at introducing students, junior faculty members, and young researchers to important theories and applications of data visualization, statistical and mathematical modeling, and various mathematical tools for model analysis.  There will be seven courses which will cover a variety of topics from data modeling to in-depth analysis and mathematical justifications for data-based decision making.