Kalani Ranathunga

Kalani is a PhD researcher specialising in Physics-Informed Machine Learning (PIML) for modelling and predicting atmospheric pollutant dispersion. Her work integrates deep learning, physical laws, and real-world air-quality data to develop advanced predictive frameworks. She also contributes to life-cycle assessment (LCA) studies on low-carbon cooling technologies, supporting interdisciplinary solutions for environmental sustainability. Kalani is passionate about developing machine-learning-enhanced environmental models that support sustainable urban planning, public health, and the broader vision of healthy people and a healthy planet.