Australian Research Council Fellow Develops Mathematical Models for Biological Growth

In a significant advancement for the fields of biology and computational modeling, Professor Hamid Laga from Murdoch University has been awarded a prestigious Australian Research Council (ARC) Future Fellowship. This grant, totaling $1,276,884, will support a four-year project focused on the mathematical modeling of how living organisms develop their three-dimensional (3D) shapes, grow, and deform in response to environmental interactions.

The importance of this project is underscored by its potential implications for understanding developmental processes, natural growth, and the progression of diseases. According to Professor Laga, the project aims to create innovative mathematical tools and machine learning algorithms that can analyze biological forms and their changes over time. “We will develop a new generation of neural networks that are not only physically motivated but also compact and efficient to train,” he stated during his announcement on July 15, 2025.

The ARC Future Fellowships scheme is designed to bolster high-quality research by mid-career researchers in areas of national and international significance. This year, the Australian Government allocated $114.6 million to support 100 researchers across various fields. The funding reflects the government’s commitment to fostering excellence in research, particularly in domains that align with national research priorities.

Professor Laga’s project is poised to yield substantial benefits across multiple disciplines. In the realm of medical diagnostics, the ability to statistically model 3D deformations of the human body can provide valuable insights into degenerative neurological diseases, where abnormalities in body motion often serve as early indicators. Additionally, the proposed computational tools will facilitate the differentiation between normal biological growth and pathological changes, thereby improving predictive accuracy regarding growth trajectories.

The project's anticipated outcomes include the development of techniques that can directly operate on RGB images and videos, which could revolutionize fields such as computer vision and graphics. This is particularly relevant in the context of analyzing dynamic biological processes, where traditional methods may fall short.

As Professor Laga articulates, “The techniques we develop will be crucial for advancing our understanding of various biological phenomena and could lead to groundbreaking discoveries in health and disease management.”

The research is aligned with broader trends in the integration of machine learning and biological sciences, which have seen a surge in interest in recent years. With the growing complexity of biological data, innovative mathematical approaches are essential for extracting meaningful insights and improving our understanding of life sciences.

In conclusion, Professor Laga’s work exemplifies the intersection of mathematics, biology, and technology, highlighting how interdisciplinary research can lead to significant advancements in our understanding of life and health. As the project unfolds, it promises to reshape existing paradigms in biological modeling and contribute to the development of new diagnostic tools and techniques that enhance our ability to understand and address health-related challenges.