My research focuses on machine learning, computational modelling, and data-driven analysis of complex systems, with an emphasis on developing scalable and interpretable methods for real-world applications. I design algorithms and computational frameworks that integrate AI, statistical modelling, and intelligent sensing to analyse large-scale and high-dimensional datasets.

A key aspect of my work is the use of sensor networks, IoT systems, and remote sensing data to model dynamic processes in complex environments. This includes developing data-driven approaches for pattern recognition, predictive modelling, and system optimisation in distributed and data-rich contexts.

My research contributes to advancing AI-enabled decision support and intelligent systems, with applications in areas such as environmental monitoring, infrastructure systems, and large-scale data analytics. I am particularly interested in interdisciplinary research that combines machine learning, computational science, and real-world data systems to address complex societal and technological challenges.