Coursework and projects in data science, programming, statistics, policy analysis, and computational methods.
I am a graduate student in Computational Analysis and Public Policy at the University of Chicago, with a background in economics, public policy, and data analysis. I am interested in using data, code, and research to understand real-world problems and build tools that are both technically strong and socially meaningful.
My work sits at the intersection of policy and computation. I have worked on projects involving machine learning, survey analysis, web scraping, data cleaning, visualization, and applied research. I enjoy building projects that turn messy real-world data into something useful, interpretable, and decision-relevant.
Right now, I am especially interested in computational social science, public-interest technology, and data-driven policy analysis.
Coursework and projects in data science, programming, statistics, policy analysis, and computational methods.
Coursework in econometrics, mathematical economics, time series analysis, and development economics.
Worked on applied research using data and predictive methods, contributing to projects with policy relevance in education and social outcomes.
Supported survey-based research by cleaning, organizing, and analyzing data for policy and research use.
Worked with business and marketing data to identify patterns, track performance, and support data-driven decisions.
Built a project comparing what U.S. presidential candidates talked about in campaign speeches with the issues voters said mattered most during the 2016, 2020, and 2024 election cycles. The project combined polling data, text analysis, and interactive visualizations to explore alignment between public priorities and campaign rhetoric.
My work included data cleaning, combining datasets, structuring project outputs, and helping build visualizations for the final dashboard.
Contributed to a project focused on modeling school enrollment and education-related outcomes in Pakistan. This work involved large-scale data, predictive methods, and policy-oriented interpretation. It strengthened my interest in building computational tools that can support public decision-making.
Across different research and analyst roles, I have worked on cleaning survey data, organizing datasets, producing summaries, and supporting projects that connect data analysis with real-world policy and operational questions.
I am interested in opportunities in data science, research, computational social science, and public-interest technology, especially roles where I can work on meaningful problems with strong technical teams.