Survey Design

Claudia Natalia von Vacano, Ph.D.

Founding Executive Director and Principal Investigator

Dr. Claudia Natalia von Vacano is the Founding Executive Director and Senior Research Associate of UC Berkeley’s Social Sciences Data Laboratory (D-Lab), including the Berkeley Federal Statistical Research Data Center. Her work advances interdisciplinary approaches to computational research, data science education, digital humanities, and trustworthy AI.

At D-Lab, Dr. von Vacano leads programs that support computational and data-intensive research through training, consultations, working groups, courses, and cross-campus collaboration....

Scarlet Sands-Bliss

Data Science & AI Fellow 2025-2026, Domain Consultant, Research IT
School of Public Health

Scarlet Bliss is an MS/PhD student in Epidemiology in the School of Public Health. Her work focuses on mixed methods approaches to characterizing and preventing spread of antimicrobial resistance and other enteric pathogens via the environment. She has experience in statistical analysis and public health bioinformatics. She is interested in ethical use of big data as it relates to epidemiologic research.

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

November 19, 2025
Sarah Daniel
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.

Lance Santana

Consulting Drop-In Hours: By appointment only

Consulting Areas: APIs, ArcGIS Desktop - Online or Pro, Bayesian Methods, Cluster Analysis, Data Visualization, Databases and SQL, Excel, Git or GitHub, Java, Machine Learning, Means Tests, Natural Language Processing (NLP), Python, Qualtrics, R, Regression Analysis, Research Planning, RStudio, Software Output Interpretation, SQL, Survey Design, Survey Sampling, Tableau, Text Analysis

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

Alyssa Heinze

Consulting Drop-In Hours: By appointment only

Consulting Areas: Causal Inference, Data Visualization, Experimental Design, Focus Groups and Interviews, Git or GitHub, LaTeX, Machine Learning, Meta-Analysis, Mixed Methods, Qualitative Methods, Qualtrics, R, Regression Analysis, Research Design, RStudio, STATA, Survey Design, Text Analysis

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

Aidan Lee

Consulting Drop-In Hours: By appointment only

Consulting Areas: ArcGIS Desktop - Online or Pro, Bayesian Methods, Causal Inference, Cluster Analysis, Data Sources, Data Visualization, Databases and SQL, Digital Health, Excel, Experimental Design, Geospatial Data: Maps and Spatial Analysis, Git or GitHub, LaTeX, Machine Learning, Means Tests, Mixed Methods, Natural Language Processing (NLP), OCR, Python, Qualtrics, R, Regression Analysis, Research Design, Research Planning, RStudio, RStudio Cloud, SAS, Software Output Interpretation, SPSS, SQL,...

Jonathan Pedroza (JP)

Postdoctoral Scholar
Berkeley School of Education

JP is a postdoctoral scholar in Data Science Education. He received his PhD in Prevention Science from the University of Oregon. His research interests include: examining risk and protective factors of health disparities in Latina/o/x/e populations and investigating educational outcomes in underrepresented student populations. JP uses a social-ecological framework to address his research interests.

Previously, he has served as an adjunct lecturer at Cal Poly Pomona teaching research methods and statistics, as well as a data scientist at the University of Kansas' Accessible Teaching...

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.

Weiying Li

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

Weiying is a Ph.D. candidate in Learning Sciences and Human Development at the UC Berkeley School of Education, with a Designated Emphasis in New Media. Her research focuses on designing and evaluating AI dialogs that support students in learning complex science concepts and engaging with social justice topics in science, such as food access. She uses mixed methods to investigate how iterative prompt design, developed in collaboration with teachers, can deepen students’ knowledge integration. Her work contributes to the development of responsible and adaptive AI tools for...

Field Experiments in Corporations

January 28, 2025
Yue Lin
by Yue Lin. How do social science researchers conduct field experiments with private actors? Yue Lin provides a brief overview of the recent developments in political economy and management strategy, with a focus on filing field experiments within private corporations. Unlike conventional targets like individuals and government agencies, private companies are an emergent sweet spot for scholars to test for important theories, such as sustainability, censorship, and market behavior. After comparing the strengths and weaknesses of this powerful yet nascent method, Lin brainstorms some practical solutions to improve the success rate of field experimental studies. She aims to introduce a new methodological tool in a nascent research field and shed some light on improving experimental quality while adhering to ethical standards.