Diversity in Data

Diversity in Data topic

A Participant-Centered, GIS-Based Approach to Improving Contextual Measurement

November 19, 2025
by Sarah Daniel. Researchers increasingly recognize that neighborhoods profoundly shape life outcomes, yet measuring them remains challenging. A common approach uses administrative boundaries, such as census tracts, as proxies for neighborhoods, but this method presents three key challenges. First, administrative boundaries may fail to capture residents’ lived experiences, a limitation that is particularly concerning in marginalized communities; second, they can misrepresent contextual effects; and third, they may produce inconsistent findings. To address these issues, I advocate for the use of self-defined neighborhood boundaries as an alternative measure. I compare GIS- and non-GIS-based methods and propose that GIS-based methods offer the strongest potential for more valid measurement.

Umesh Singla

Consulting Drop-In Hours: By appointment only

Consulting Areas: Bash or Command Line, Bayesian Methods, Causal Inference, Data Visualization, Deep Learning, Diversity in Data, Git or GitHub, Hierarchical Models, High Dimensional Statistics, Machine Learning, Nonparametric Methods, Python, Qualitative Methods, Regression Analysis, Research Design

Quick-tip: the fastest way to speak to a consultant is to first ...

Sharazad Ali

Consulting Drop-In Hours: By appointment only

Consulting Areas: Cluster Analysis, Databases and SQL, Data Visualization, Diversity in Data, Excel, Experimental Design, Focus Groups and Interviews, Machine Learning, Means Tests, Python, Qualitative Methods, Qualtrics, R, Regression Analysis, RStudio Cloud, Software Output Interpretation, SQL, Time Series

Quick-tip: the fastest way to speak to a consultant is to first ...

Why I Don’t Call Myself a Data Scientist: A Researcher's Journey

October 1, 2025
by Jose Aguilar. I reflect on my uneasy relationship with being called a data scientist. Despite training in computer science and utilizing computational tools in education policy, I struggle with how data science often strips away human narratives and reinforces existing inequities. My identity as a first-generation, queer, Latinx scholar deepens these tensions, prompting me to explore frameworks such as QuantCrit and critical data science. Ultimately, I utilize research that bridges computation and critique, advocating for more human-centered, politically aware approaches to data that integrate lived experiences alongside data findings.

Jose Aguilar

Data Science & AI Fellow 2025-2026
Berkeley Graduate School of Education

Jose R. Aguilar is currently a PhD student in the Policy, Politics, and Leadership program at UC Berkeley’s School of Education. His research utilizes natural language processing, machine learning, and social network analysis to investigate how institutional discourse, algorithmic decision-making, and education policy influence postsecondary access and equity for marginalized students. Before Berkeley, Jose earned his M.A. in Urban Education from Loyola Marymount University and dual B.A./B.S.A. degrees in Government, Latina/o Studies, and Computer Science from the University of...

Sarah Daniel

Data Science & AI Fellow 2025-2026
Political Science

Sarah Daniel is a PhD candidate in Political Science, specializing in urban politics in Sub-Saharan Africa, with a particular focus on East Africa. Her research examines how neighborhood communities organize for collective action to improve service delivery, reduce inequality, and enhance political representation.

Armaan Hiranandani

Data Science & AI Fellow 2025-2026
School of Information

Armaan Hiranandani is a Master’s student in Data Science at UC Berkeley, where he also earned his B.S. in Industrial Engineering & Operations Research. Born and raised in Dubai, Armaan recently completed a software engineering internship at Netflix, working on the machine learning platform team. His interests include building scalable AI systems and applying data science to solve real-world problems.

Abby O'Neill

Data Science & AI Fellow 2025-2026
Electrical Engineering and Computer Sciences (EECS)

I'm a PhD student in Berkeley AI Research (BAIR). My research interests include interpretability, robotics, computer vision, AI for the environment, and education, though the list keeps growing and probably needs some pruning. I'm a little nervous, but mostly hopeful about the future we're building and about the role data plays in shaping it.

Why Data Disaggregation Matters: Exploring the Diversity of Asian American Economic Outcomes Using Public Use Microdata Sample (PUMS) Data

February 11, 2025
by Taesoo Song. Asian Americans are often overlooked in discussions of racial inequality due to their high average socioeconomic attainment. Many academic and policy researchers treat Asians as a single racial category in their analysis. However, this broad categorization can mask significant within-group disparities, leaving many disadvantaged individuals without access to vital resources and policy support. Song emphasizes the importance of data disaggregation in revealing Asian American inequalities, particularly in areas like income and homeownership, and demonstrates how breaking down these categories can lead to more targeted and effective policy solutions.

Teaching Data Science as a Tool for Empowerment

February 18, 2025
by Elijah Mercer. Data literacy is a powerful tool for empowerment, especially for historically marginalized communities. Through Data Cafecito at Roadmap to Peace and helping teach Data 4AC at UC Berkeley, Elijah Mercer helps bridge the gap between data, advocacy, and justice. Data Cafecito fosters culturally responsive data practices for Latinx-serving organizations, while Data 4AC challenges students to critically analyze data’s role in systemic inequities. Drawing from his experience in education, Mercer uses interactive teaching methods to make data accessible and meaningful. By centering storytelling and community-driven insights, he aims to equip individuals with the skills to use data for social change.