Topics

The key themes include, but are not limited to: 

Topic 1:

• Mathematical modeling of AI algorithms.
• Optimization strategies for machine learning.
• AI-powered solutions to practical mathematics problems.
• Computational Intelligence and numerical approaches.
• Theoretical perspectives on data science and AI approaches.
• Deep Learning et Machine Learning.
• Natural Language Processing.
• Generative AI.
• Signal Processing and Image.
• AI for IoT.
• AI for Climate and Environmental Sciences.

Topic 2:

• Biomathematics.
• Computing in Mathematics.
• Computational Approaches to PDEs.
• Control Theory and Applications.
• Dynamical Systems.
• Evolution Equations.
• Harmonic Analysis.
• Mathematical Biology and Ecosystems Modeling.
• Modelling and Engineering.
• Neural Networks.
• Nonlinear Dynamics.
• Numerical Analysis.
• Optimization and PDE Systems. 

P.S.: the list is not exhaustive