I’m passionate about Economics and Data Science, with a strong interest in using data-driven approaches to understand and address real-world problems. My work spans economics, machine learning, geospatial analytics, and financial analytics, where I focus on building projects that combine rigorous analysis with practical applications.
- Panel data analysis and causal inference using R and Python
- Mapping environmental change using machine learning, econometrics, and remote sensing
- Developing computational tools for data collection and processing in economic and policy research
- Applications of applied machine learning in economics and policy research
- Bayesian methods for inference and predictive modeling
- Advanced Deep learning and its applications in academic research and business problem-solving
- Data-driven analysis of markets, competition, and firm behavior using structural econometric techniques