2025 Internship Project Overview

I built and deployed a web app that visualizes city-level air pollution data in India to quantify the efficacy of government policies over time. To do so, I first built a web scraper to collect pollution time series data from India’s Central Pollution Control Board. Next, I reduced missing-data bias by performing bias simulations on Princeton’s Della cluster. Finally, I performed a plethora of exploratory analyses of the data: I isolated emissions trends from historical weather patterns with machine learning (random forest models), used statistical methods to assess the individual effects of weather variables on pollution time series, cross-validated the particulate matter time series with satellite measurements and produced city-level mortality metrics.

ORGANIZATION/RESEARCH GROUP

Center for Policy Research on Energy and the Environment (C-PREE), School of Public and International Affairs, Princeton University

LOCATION

Princeton, New Jersey

 

Interns

Thomas Zhang ’28
Major: Electrical and Computer Engineering
Minor(s): Statistics and Machine Learning
"The internship provided me with endless opportunities to learn in an interdisciplinary manner, bridging software development, machine learning, atmospheric chemistry, and policy. I found the experience of doing research to be interesting in itself because of how much it subverted my expectations—C-PREE in particular is constantly seeking to innovate and to integrate knowledge across fields and disciplines. This internship definitely convinced me to continue pursuing research opportunities throughout my career at Princeton and beyond, and towards the idea of grad school."

Click to view the end-of-project presentation

 

Denise Mauzerall
William S. Tod Professor of Civil and Environmental Engineering and Public and International Affairs

Mentors

  • Yuanyu Xie, Associate Research Scholar, Princeton School of Public and International Affairs