Numerical Simulations and Machine Learning Algorithms of Complex Systems

Dear Colleagues,

Today, the massive leap in computing power has shifted numerical simulations and machine learning (ML) from being just “support tools” to becoming the primary engines of scientific discovery. These methods provide a much-needed framework for deconstructing the hidden complexities within various systems. Whether we are looking at environmental shifts, how the human body performs under stress, or the technical hurdles in engineering, combining mathematical precision with data-driven insights is no longer optional—it is essential.

This Special Issue is designed as a cross-disciplinary space for research that sits at the intersection of numerical modeling and ML. We are particularly interested in seeing how “state-of-the-art” techniques can be used to handle the messiness of real-world data, such as non-linearity and high-dimensional variables that traditional models often struggle with.

With our new, broader scope, we are excited to invite contributions that bridge these methods with Sports Science and Human Movement, in addition to our core interest in engineering and environmental modeling. We welcome both original research and deep-dive reviews that aim to push the limits of what is possible in healthcare, technology, and applied mathematics.

The scope includes, but is not limited to, the following:

• Human Systems & Sports Science: Using ML for biomechanics, predicting athletic outcomes, and simulating physiological responses.
• Environmental & Earth Systems: Hybrid numerical-ML approaches for modeling the atmosphere, water systems, and geological changes.
• Biomedical & Healthcare: Data-driven insights for clinical decisions and simulating how biological processes or diseases evolve.
• Engineering & Technical Systems: Solving problems in fluid dynamics, structural mechanics, and optimizing smart technologies.
• Theoretical Foundations: Developing new ML algorithms that respect physical laws to make predictions more accurate and efficient.

Dr. Nopparat Pochai
Guest Editor

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