I'm Michael Rosenbaum, a Masters candidate at the University of Chicago, studying Computer Science and Public Policy. Before this, I worked for almost a decade advising nonprofits and governments on how to monitor and evaluate the effectiveness of their programs. I focus on public benefit programs. Formally at Innovations for Poverty Action and the Behavioral Insights Team.

For more information, please reach out over email or through LinkedIn.

• 🚍 Bus Pending (2023 | Python, SQLite3): Scraped and analyzed 4.5 million bus-minute observations to measure inequality in Chicago Transit Authority bus delays with 3 classmaters.
• 💸 Predicting Poverty using a Proxy Means Test (2024 | Python): Constructed a proxy means test to predict income categories from Costa Rican household survey data using supervised machine learning techniques.
• 🏫 Teacher Mobility in CPS (2018 | R, Stata): Example statistical code that scrapes and analyzes teacher employment data to show the effect of principal changes on teacher attrition using a synthetic control model.

Many repos for school projects are private to follow academic honesty policies. Code for any of the below is available on request:

• CAPP 121: Computer Science with Applications I (Python)
  • Implementing a SIR model of epidemic spread (Functional Programming Basics): Control flow statements; data types
  • Modeling housing segregation using a schelling model (Decomposition): Functions; automatic testing.
  • Analyzing candidate tweets using a bag of words model (Dictionaries): Importing files; dictionaries; nested dictionaries; k-mers; abstraction
  • Modeling election wait times (Classes & Objects): Stacks; queues; object-oriented programming; attributes; methods
  • Creating a treemap (of ornithological data) (Recursion): Trees; recursion; binary search.
  • Summarizing airline delay data (NumPy): Cleaning data in NumPy; modifying units of analysis; arrays.
• CAPP 122: Computer Science with Applications II (Python)
  • Similarity of political speeches (Implementing an open addressing hash algorithm): virtual environments; hash tables; abstract classes; interfaces
  • Creating a databse of Chicago parks (Web scraping): HTTP requests, scraping, CSS/XML selectors, APIs, JSON formatting
  • Creating a front-end query interface (Querying in SQL): Basic RDBMS structure; SQL queries; preventing injection
  • Matching PPP data to political donations (Data linkage): Regular expressions; data linkage; efficiency optimization; test-driven development; Pandas
  • Predicting school performance (Predictions): Decision trees, test/train split; information gain; optimization; Pandas
• CAPP 235: Databases for Public Policy (Python; SQL)
  • Storing and cleaning restaurant inspections (REST API with Flask): REST APIs; Flask servers; data linkage; POST / GET operations with a web front-end

Academic publications

• Glazerman, S., Grépin, K. A., Mueller, V., Rosenbaum, M., & Wu, N. (2023). Do referrals improve the representation of women in mobile phone surveys?. Journal of Development Economics, 162, 103077.

Working papers and technical guidance

• Collins, E., Warren, S., Lamke, C., Contreras, I., Henderson, S., & Rosenbaum, M. (2023). Representativeness of Remote Survey Methods in LMICs: A Cross-National Analysis of Pandemic-Era Studies. Working paper.
• Bogicevic, B., Das, N., Davies, E., Dillon, A., Glazerman, S., & Rosenbaum, M. (2021). Assessing Repeated and Rescheduled Attempts in Random Digit Dial Surveys. Global Poverty Research Lab Working Paper, No. 21-110.
• Das, N., Davies, E., Dillon, A., Glazerman, S., & Rosenbaum, M. (2021). Optimal Timing for Random Digit Dialing. Global Poverty Research Lab Working Paper, No. 21-107.
• Dillon, A., Glazerman, S., & Rosenbaum, M. (2021). Messaging to Improve Response Rates: Effectiveness of Pre-Survey SMS Messages. Global Poverty Research Lab Working Paper, No. 21-106.
• Dillon, A., Glazerman, S., & Rosenbaum, M. (2021). Understanding Response Rates in Random Digit Dial Surveys. Global Poverty Research Lab Working Paper, No. 21-105.
• Henderson, S. & Rosenbaum, M. (2020) Remote Surveying in a Pandemic: Research Synthesis. Innovations for Poverty Action: Working Paper.
• Glazerman, S., Rosenbaum, M., Sandino, R., Shaughnessy L. (2020). Remote Surveying in a Pandemic. Innovations for Poverty Action: Working Paper.