Machine Learning and Mathematical Modelling for Data Science and Applications

Dear Colleagues,

In today’s data-rich and computation-driven world, machine learning has become a central tool for extracting structure and insight from complex systems. At the same time, the growing scale and complexity of modern learning models demand mathematically principled approaches that go beyond empirical performance and address fundamental issues of modeling, analysis, and reliability. This Special Issue explores advanced machine learning techniques developed within rigorous mathematical modeling frameworks, with relevance to data science applications in health, environmental systems, and sustainable living.

The focus of this Special Issue will be on the mathematical foundations of contemporary learning paradigms, including deep learning, neuro-fuzzy models, graph neural networks, and large language models (LLMs). Authors are encouraged to examine these methods through formal modeling, theoretical analysis, or computational mathematics, addressing questions such as representation, learning dynamics, optimization, stability, and generalization. Work that clarifies the mathematical structure of learning models or provides interpretable and theoretically supported formulations is particularly welcome.

Special attention is also given to settings involving complex and heterogeneous data, such as multimodal healthcare, where mathematical modeling is essential for integrating diverse data sources and managing uncertainty. Similar challenges arise in environmental and sustainability-oriented applications, where data-driven models must respect structural, physical, or systemic constraints.

This Special Issue aims to bring together mathematically grounded contributions that advance machine learning theory while offering meaningful insights on contemporary data science problems.

Dr. Maybin K. Muyeba
Guest Editor

Manuscript Submission Information

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Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.