Yiteng Zhang is currently engaged in research on coastal blue carbon ecosystems, with a particular focus on mangrove forest health assessment and carbon estimation. His work integrates UAV-based remote sensing, object-level image recognition, and machine learning techniques, such as CatBoost modeling and SHAP interpretability analysis. He has experience applying DTW-based trajectory similarity analysis and OPTICS clustering to environmental pattern extraction, and has contributed to multi-source data integration, species classification, and ecological factor detection in complex monitoring systems. His recent publication in Forests explores a stand structure-based framework for evaluating urban mangrove forest health, emphasizing scalable indicators and high-resolution canopy segmentation.