Urban Studies Departmental Research Program

About: Prior research has established a strong link between racist attitudes and opposition to affordable housing. In recent years, racial language around affordable housing has become more covert in contexts such as media depictions of proposed developments.  This project aims to: (1) leverage a racial meaning decoding framework, grounded in theories of covert racism and informed by empirical instances of coded race talk, to identify racial code words in news articles focused on affordable housing, and 2) link the occurrence of the code words identified in these news articles, to changes in affordable housing stock over time in the geographic regions of the news outlets. We hypothesize that when coded and explicit racial language appear more frequently in news coverage of affordable housing, it reflects lower public support, which is not easily measured longitudinally, and which in turn results in a decrease in the successful development of new affordable housing units. We will explore manual and automated methods for identifying the racial code words in our newspaper corpus, including qualitative hand coding and natural language processing (NLP) algorithms.

Research Tasks: Tasks may include but are not limited to: (1) conducting literature reviews on affordable housing, sustainability, and public policy, (2) collecting, organizing, and analyzing a news article corpus (no coding experience needed; training will be provided in R and or Python for basic data analysis), and (3) learning to give clear presentations and provide brief write-ups of their work.

Qualifications: Preferred coding experience (Python, R) but not required. 

Apply in SOLO here.

About: In response to police withdrawal and the harms of punitive policing, U.S. cities are experimenting with civilian-led safety initiatives. However, rigorous causal evidence of their effectiveness remains scarce. One of the most prominent programs is Urban Alchemy (UA) in San Francisco, which deploys unarmed “civilianized safety practitioners” at high-crime intersections to provide presence, de-escalation, and service referrals. UAs workforce are credible messengers whose lived experience with incarceration, addiction, homelessness, and extreme poverty allows them to build trust and intervene in ways police cannot. Significant reductions in total crime and behavioral health-related crimes at intersections with UA practitioners has been observed offering rare empirical support for non-police safety models rooted in trust and human connection. Yet not every intersection sees declines, raising our central research question: why do some UA sites succeed while others do not? Our project addresses this question by developing an AI-driven field system that integrates sound and computer vision to identify the mechanisms of UA’s impact.

Research Tasks: Tasks may include analyzing (1) vocal recordings for stress detection to understand number, timing, and effectiveness of interactions, (2) other ambient "acoustic signatures" -- like ratios of biophony (nature) vs. anthrophony (human/traffic) and public safety cues (e.g., sirens, alarms), and (3) urban form and disorder through visual markers captured through privacy–preserving cameras and computer vision.

Qualifications: Coding/digital hardware experience preferred (CS/EE major would be ideal but not required)

Apply in SOLO here

About: This project develops an automated system to generate a fine-grained dataset on cartel presence, power, and modus operandi across Mexico. Building on prior research that manually compiled data on organized crime activity, the current phase seeks to leverage Large Language Models (LLMs) and machine learning (ML) techniques to extract, classify, and validate information from diverse textual and media sources. The goal is to create a state-of-the-art, reproducible dataset that enhances both the temporal and spatial precision of our existing cartel presence data.

Research Tasks: The undergraduate Research Assistant (RA) will support the automation and refinement of our cartel presence dataset. Under the supervision of the research team, the RA will implement and test computational methods for information extraction, entity recognition, and classification using both supervised and unsupervised approaches. The RA will also help evaluate and document the outputs of language models, ensuring accuracy, transparency, and replicability of results.

Key Responsibilities:

• Data Collection and Preprocessing
• Gather and clean textual data from public sources (e.g., news archives, government reports, social media, or NGO bulletins).
• Format and preprocess text data for machine learning pipelines (tokenization, normalization, metadata tagging).
• Assist in developing scripts for automated data retrieval or web scraping (where ethically and legally permissible).
• LLM and ML Model Development.
• Implement and fine-tune LLM-based methods for entity recognition (e.g., identifying cartels, locations, events).
• Develop or assist in training ML models for text classification and clustering related to cartel activity.
• Compare performance across models (e.g., GPT, Claude, fine-tuned BERT variants) and document evaluation metrics.
• Validation and Quality Assurance.
• Conduct manual validation of model outputs to ensure reliability and reduce false positives/negatives.
• Contribute to the creation of a benchmark or “gold standard” subset of validated data.
• Use visualization and descriptive statistics to summarize results and identify model biases or gaps.
• Documentation and Collaboration.
• Maintain clear documentation of workflows, data preprocessing steps, and model configurations.
• Contribute to GitHub repositories, including version control, code commenting, and README updates.
• Participate in weekly research meetings to discuss progress, challenges, and methodological improvements.

Qualifications:

• Strong programming skills in Python (preferred libraries: pandas, scikit-learn, transformers, spaCy, or OpenAI API).
• Familiarity with machine learning, natural language processing, or data science workflows.
• Coursework or demonstrated interest in computational social science, political science, data analysis, or Latin American studies.
• Attention to detail, strong organizational skills, and commitment to research ethics.

Apply in SOLO here.

About: In Europe, drowning emerged as a notable form of accidental death in the mid-18th century. “Apparently drowned” bodies, teetering between life and death, presented objects of fear, revulsion, and fascination and advocates faced intense religious and scientific resistance in addition to their own organizational, educational, medical, and financial challenges. I have been writing an interdisciplinary cultural analysis of the rise of drowning advocacy and medicine from 1774 to the present. Coming to conclusion after five years, I am applying for funding for a student to assist with the final elements of the project, which includes a scholarly book and a gallery show (scheduled for the Green library in Winter 2027.)

Research Tasks: By summer 2026, the manuscript will be complete and in final preparation for publication. The student will be engaged in (1) the preparation of the final book manuscript, which will involve attainting and finalizing image permission, photoshopping and finalizing all art images and captions, finalizing bibliographic materials and records, fact-checking, and (2) assistance with curatorial details of the gallery show including design, organizations, publicity, and catalogue preparation.Qualifications: The RA should be an upper level undergraduate with research experience and attention to detail. 

Apply in SOLO here.

About: This project will produce a public-facing online resource - a repository of scholarship, writing, visual and video representations, and varied primary sources accessible to a global public - that illuminates the history of Cap-Haïtien, Haiti a significant yet understudied town in modern world history. Haiti in global history is often imagined as two extremes - a utopian promise of abolition, of slaves wresting their freedom and establishing a republic, a beacon for pathways to dismantle colonialism or a dystopia imbued with violence, political chaos, poverty, and environmental degradation. These diametrically opposed representations center particularly on one locale – Cap-Français which served as the capital city of the Saint-Domingue colony in the centuries of French colonial rule. The port town was renamed Cap-Haïtien after the Haitian Revolution originated there in the late eighteenth century and the establishment of independence in 1804. These depictions are typified by the 18th century nomenclature of the city as the “Paris of the Antilles” with its economy and society fueled by slavery, rum, and sugar and its cameo appearance in the 2022 blockbuster movie Wakanda Forever as the birthplace and refuge of a future king of Wakanda, an African locale devoid of colonialism and mastering mineral resources and technologies. In Haitian accounts, au Cap, as it is called is the cradle of the revolution that bore the nation, a restive site of coups and counter coup’s in the nation’s history of contested regime changes, and a city of poets and writers. Yet, decades of uncertainty have made it so that primary sources to map and narrate a biography of the city and its inhabitants have been lost and dispersed. In tracking down, sorting, and making visible sources, this project will serve as a foundation not only for a book project on the social and political history of the city, but also for future reference by scholars and students. 

Research Tasks: RA will conduct research at: Stanford-based institutions such as The Hoover and Green Libraries; online research on the holdings of New York Public Library, Brown University Library, The University of Puerto Rico ; Archives of Overseas France; the British Library; Duke University Library; the Universities of Florida and Miami; and varied Catholic and Protestant missions. They will create a comprehensive bibliography and useable data base of publications, and visual, and audio sources in 18th-mid 20th century history of Cap-Haïtien.They will assist professor Jean-Baptiste in creating a website that charts the source materials, as well as findings from people and historical projects taking place in Haiti and elsewhere in the world on Cap-Haïtien. The site will serve as a hub to disseminate research and connect people wishing to conduct their own research.

Qualifications: Reading knowledge of French and/or Spanish useful but not necessary. Curiosity, tenacity, and attention to detail. Ability to analyze and synthesize qualitative, artistic, and quantitative information. Capacity to learn how to create a website, use geospatial and/or AI tools.

Apply in SOLO here.

About: How has the Cape Town's infrastructure evolved since the mid-19th century? How can we visualize the city's history via maps? What, in particular, can we learn from maps about the impact of apartheid's Group Areas legislation, passed in the 1950s and implemented until 1990? This project focuses on the city's evolution through detailed analysis (including georeferencing) of maps and city plans. We'll examine and curate a wide range of historic maps. Among our source material will be unpublished maps and plans in the possession of the City of Cape Town's Directorate for Spatial Planning and Environment.This project will be directly supervised by the faculty lead in partnership with the City of Cape Town; the David Rumsey Map Center; and the Stanford Geospatial Center.

Research Tasks: The RA will study various maps and plans of Cape Town, from the mid-19th century to the present day, to understand the evolution of urban space.

Qualifications: 

• Required: interest in urban history; in the history of (South) Africa.
• Preferred: experience with ArcGIS/QGIS, and with historic maps.

Apply in SOLO here.

Abstract: The Educational Opportunity Project (EOP) at Stanford University uses and generates a range of data on educational conditions, contexts, and outcomes to help scholars, policy makers, educators, and the general public learn about the landscape of educational opportunity and academic achievement in the US. The EOP houses multiple initiatives that undergraduate researchers support: 1. The Stanford Education Data Archive (SEDA): SEDA is the first 11-year national database of academic performance based on nearly 450 million 3-8th grade math and reading and language arts test scores from the 2009-2024 school years.  2. The Segregation Explorer: SegX is initiative jointly run by Professor Reardon and Professor Ann Owens at UCLA to compile and monitor school and neighborhood segregation from the 1970s through today. 3. The Kindergarten Readiness Initiative: The KRI is an initiative to develop a comparable database of kindergarten readiness assessment data for school districts across the country.

Research Tasks:

• The EOP RA will be responsible for assisting on current research projects using data from the Stanford Education Data Archive (SEDA), the Segregation Explorer, and the Kindergarten Readiness Initiative.
• The RA may also have the opportunity to research and prepare a report on their own topic of interest related to the work of the EOP – recent topics include the building a database of publications using SEDA data and link Edible Schoolyard Program participation data to SEDA.
• Specific tasks include: conducting background research on relevant topics and writing literature reviews; collecting, cleaning, and organizing data for analyses; producing memos and data reports for various projects; collaborating with EOP research staff, partners, and other RAs; and outreach (via email, phone, and conference calls) to stakeholders.

Qualifications: Interest in education, education policy, and social and educational inequality is desirable. Quantitative skills, such as data cleaning, data analysis, and programming in Stata also desired but not required. Strong ability to work independently, comfort taking initiative, and attention to detail is an asset.

Apply in SOLO here.