PhD student Mirza Md Tasnim Mukarram has recently co-authored a research article in the International Journal of Environmental Science & Technology (Springer), titled "Advanced hybrid ensemble learning models for atmospheric humidity prediction: an environmental monitoring solution in arid regions." The study proposes an advanced hybrid ensemble learning framework (HELMs) integrating Random Forest, XGBoost, LightGBM, and Gradient Boosting Regression to improve long-term atmospheric humidity prediction for a highly climate-vulnerable arid region. Congratulations, Mirza!

Read the article at the link.