His research lies at the intersection of agricultural production, environmental sustainability, and applied econometrics, with a focus on dairy systems. He studies the joint production of desirable and undesirable outputs such as milk, greenhouse gas emissions, and nutrient surpluses using frontier methods and machine learning to quantify efficiency, trade-offs, and marginal abatement costs. His work contributes to the literature by integrating by-production stochastic frontier models with flexible dependence structures and predictive approaches to better capture heterogeneity across farms. The goal of his research is to provide policy relevant evidence for designing more targeted and cost effective environmental regulations in agriculture. He is currently a visiting researcher at the University of California, Davis. Nur holds an MSc in Environmental Economics from Wageningen University & Research and an MSc and BSc in Agricultural Economics from Sylhet Agricultural University, Bangladesh.