I am a Ph.D. student in Environmental Science at the University of Manchester, with a focused research agenda on leveraging generative AI and physics-informed deep learning (PINNs) to address complex urban climate challenges. Positioned at the intersection of climate science and data-driven modeling, my work explores the transformative capabilities of generative frameworks and physically grounded neural networks in advancing urban climate understanding. Specifically, my research develops physics-guided deep learning approaches to characterize urban surface-atmosphere interactions; integrates machine learning with numerical climate models to improve the representation of urban morphology; and employs generative AI models to simulate adaptive urban climate scenarios with high spatial fidelity and physical realism.