I am a PhD researcher in Empirical Industrial Organization and Applied Microeconomics, specializing in analyzing firms’ strategic decision-making using a combination of structural econometric methods and machine learning models.
A selection of my work in academic research and data science. I use econometric and machine learning models to analyze firm behavior and market dynamics.
This research decodes why firms delay technology adoption decisions, given the stiff competition and market dynamics in the smartphone industry.
A novel approach combining econometric demand models with machine learning to optimize product portfolios, enhancing prediction accuracy.
This study applies survival analysis to investigate the factors influencing the timing of technology adoption among firms.
I am passionate about mentorship and instruction. My teaching focuses on building strong theoretical foundations and practical, hands-on data analysis skills.
Fall 2025, Stony Brook University
An introduction to statistics and econometrics for economics, with a focus on intuition and interpretation. Students learn to estimate and analyze models, understand regression assumptions, and critically evaluate research, while gaining hands-on experience with real data and Python.
View Course PageFall 2022 - Spring 2025, Stony Brook University
A course covering the theory and application of statistics in Economics, including regression analysis, model estimation, hypothesis testing, and hands-on data analysis and computation with Python.
Summer 2023-2025, Stony Brook University
An undergraduate course teaching fundamental approaches to market structure, non-linear pricing, firm strategic decision-making, and merger analysis.
I am always interested in new research collaborations, speaking opportunities, or discussions about Economics, Data Science, and Computational Modeling.
Economist / Data Scientist / Researcher
Office
Room N618, Dept. of Economics
Stony Brook University, NY 11790