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 modeling. Yuan's work aims to improve climate models and environmental understanding, supporting climate change mitigation efforts. He bridges AI and environmental challenges, using neural networks to analyze complex climate data and make predictions. Yuan emphasizes explainable AI techniques to ensure interpretable insights, 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, Yuan develops algorithms for improved satellite data processing and monitoring of key climate indicators.