Jing Pan is a PhD student at The Hong Kong University of Science and Technology (Guangzhou). Her research focuses on weather forecasting using deep learning (DL), a purely data-driven approach that has shown strong predictive performance across various studies. However, DL models lack physical processes and interpretability, while relying heavily on training datasets—meaning they tend to perform poorly when predicting extreme events that are underrepresented in training samples. To address these challenges, Jing's research interests lie in combining DL with process-based models using a hybrid approach.