Geohazard prediction · Hydrological modelling · Physics-informed and explainable machine learning I am a PhD student at Zhejiang University (ZJU), supervised by Prof. Hongyue Sun, with joint doctoral research training at Nanyang Technological University (NTU) under the supervision of Prof. Chu Jian. I expect to complete my PhD in June 2027. My research integrates environmental observations, physical knowledge, and machine learning to improve the prediction and understanding of geohazards and hydrological processes. My work spans debris-flow susceptibility, source volumes and velocity, landslide displacement and groundwater dynamics, and catchment hydrological prediction. Across these applications, I focus on three connected themes: Physics-informed learning — incorporating physical knowledge into data-driven models of hydrological and geohazard processes. Explainable prediction — examining how environmental factors shape model predictions and relating these patterns to the underlying processes. Model generalization — evaluating predictive reliability beyond the training data, with attention to spatially structured validation. My goal is to develop accurate, physically grounded, and interpretable predictive methods that support geohazard assessment, early warning, and disaster mitigation.