Tianle Yuan, a senior research scientist at NASA GSFC/UMBC GESTAR-II, focuses on applying deep learning to climate science and weather prediction. His team uses advanced models for feature extraction, prediction, regression and generative modelling. Tianle's work aims to improve climate models and environmental understanding, supporting climate change mitigation efforts. He bridges artificial intelligence (AI) and environmental challenges, using neural networks to analyse complex climate data and make predictions. Tianle emphasises explainable AI techniques to ensure interpretable insights, which are crucial for building trust in AI-driven climate predictions. His research also integrates deep learning with physical climate models, potentially leading to more robust and accurate predictions. Additionally, he develops algorithms for improved satellite data processing and monitoring key climate indicators.