Researcher at International University of Business Agriculture and Technology
I am an interdisciplinary researcher specializing in the application of Artificial Intelligence (AI) and Machine Learning (ML) to environmental sustainability and water resource management. My research focuses on developing predictive, data-driven frameworks to address ecological challenges and support climate adaptation. Recently, I co-authored a study published in the MDPI journal Sustainability, titled "Predicting Seasonal Variations in River Water Quality: An Artificial Intelligence (AI) Approach Integrating Physicochemical Parameters." This work utilizes optimized machine learning architectures (such as XGBoost and Random Forest) alongside SHAP interpretability to forecast spatial and seasonal water quality dynamics across major river systems. On ResearchBuddy, I aim to collaborate with fellow data scientists, engineers, and policymakers to scale up intelligent environmental monitoring systems and transform complex data into actionable insights for global water security.