I am Buddhika Patalee, an applied economist and quantitative researcher. My research focuses on agricultural and production economics, risk and decision-making, consumer behavior, and applied policy analysis.
My work combines econometric methods, machine learning, and computational analytics to study complex economic questions using large and diverse datasets. I am particularly interested in production risk, climate and weather impacts, technology and resource-use decisions, and the application of advanced analytical methods to agricultural and economic decision-making.
Alongside my research in agricultural economics, I have collaborated on interdisciplinary projects in health, consumer behavior, and data science. These projects have broadened my methodological expertise in predictive modeling, causal inference, machine learning, and high-dimensional data analysis.
This website brings together my research, publications, teaching, analytical projects, and other professional work.
AI & Machine Learning Applications
My technical toolkit spans machine learning, econometrics, and applied statistics including neural networks, causal inference methods, feature engineering, and model evaluation, using Python (scikit-learn, pandas), R, SQL, and STATA. See the full technical breakdown on my Research Portfolio.
