Hye Jee Kim

SSDS Consultant

Hye Jee is a PhD student in Sociology. Her current research projects examine racial inequalities in health, racial bias, and Asian American racialization using both quantitative and qualitative methods.  

Consulting Areas: social science, data wrangling, data visualization, regression, statistics

Software/Tools: R, Stata

Nay San

SSDS Consultant

Nay San is a PhD Candidate in Linguistics. His research examines how modern speech and language technologies can be adapted for typically underserved languages and user populations, with a particular focus on supporting data management workflows for language documentation and revitalisation.
Consulting areas: speech and language processing (both text and audio), data wrangling, data visualization, deep learning, data and workflow management (e.g. archiving, reproducibility)
Software/tools: Python, R, SQL, Bash, Git / GitHub, Docker, Excel, LaTeX/Overleaf, web development (HTML/CSS/JavaScript)

Anthony Weng

SSDS Consultant

Anthony is a MS Candidate in Computer Science. As an undergrad, he majored in Economics and began work in Stanford's Digital Economy Lab, helping to investigate how technological advancements impact economic outcomes. His research experience has centered on applied data science techniques, data wrangling, and sourcing data. He enjoys weightlifting and good food otherwise.

Consulting areas: Social sciences, natural language processing, data acquisition, data wrangling

Software/tools: Python, LaTex/Overleaf

Renee Louis

SSDS Consultant

Renee Louis is a PhD student in the department of Sociology. She conducts research on housing, neighborhood inequality, and urban poverty through a mixture of quantitative and qualitative research methods. Her previous work includes tracking residential evictions during the COVID-19 pandemic through scraping publicly-available administrative records online and merging with census data. She is passionate about open science and publicly-engaged research.

Consulting areas: Data wrangling, data visualization, (some) geospatial, regression, social science, statistics, longitudinal

Software/tools: R, Stata, LaTeX/Overleaf

Tara Chiatovich

SSDS Consultant

Tara works as a research and data scientist for an education technology company after earning her Ph.D. from the Standford Graduate School of Education. Her research cuts across academics, behavior, and social-emotional learning in K-12 schools and uses both traditional statistical approaches and machine learning. She is currently analyzing survey data measuring students' social-emotional learning from before to during the pandemic to examine how trends over time changed during the schooling disruptions from COVID-19.

Consulting areas: Data wrangling, data visualization, data reduction, regression, multi-level modeling, time-series analysis

Software/tools: R, Python, Stata, SAS, Git, Excel, Qualtrics

Allex Ravenscar Desronvil

SSDS Consultant

Allex is a PhD Candidate in Sociology. His work investigates the intersection of social inequality and the sociology of law through causal inference and computational methods. His work uses publically-available datasets (such as the NHIS, Census data, etc.) and some restricted-access text data.

Consulting areas: Data wrangling, data visualization, regression, social sciences, statistics, longitudinal data

Software/tools: R, Stata, Git / GitHub, Excel, Qualtrics

Amy Lynne Johnson

SSDS Consultant

Amy is a PhD Candidate in Sociology. Her research explores the relationship between 21st century social and cultural change and individuals' subjective experiences and sensemaking. Currently, her dissertation uses computational text analysis to analyze discourse and language around mental health in the news media and on social media. Beyond research, Amy is passionate about equitable and inclusive teaching, particularly of quantitative methods and software.

Consulting areas: Data wrangling, data visualization, interviews, regression, social sciences, statistics

Software/tools: R, Stata, NVivo, Dedoose, FarmShare, Sherlock

 Evan Muzzall

Head of SSDS

I am a formally trained bioarchaeologist and forensic anthropologist who became interested in data science through the measurement of bones, stones, and archaeological sites a long time ago. I earned my PhD in Biological Anthropology from Southern Illinois University Carbondale and, before joining Stanford, was the Instructional Services Lead at the UC Berkeley D-Lab. My personal research spans functional biomechanics, mortuary archaeology, microbiology, conflict and war, teaching pedagogy, depression, perioperative complications, survey design and analysis, and machine learning. I love anything to do with dogs, music, cooking, and the outdoors.

Consulting areas: Computational text analysis, data wrangling, data visualization, deep learning, digital humanities, geospatial mapping, machine learning, natural language processing, social sciences, time series

Software/tools: R, Python, Bash, PAST, Git / GitHub, Excel, Qualtrics, Lucidchart