Databases & SQL

Stephanie Andrews

Availability: By appointment only

Consulting Areas: Python, SQL, HTML / CSS, Javascript, APIs, Databases & SQL, Data Manipulation and Cleaning, Data Science, Data Sources, Data Visualization, Digital Humanities, Machine Learning, Natural Language Processing, Software Tools, Text Analysis, Web Scraping, Bash or Command Line, Excel, Git or Github, Tableau

Theo Snow

Availability: By appointment only

Consulting Areas: Python, R, SQL, SAS, Databases & SQL, Data Manipulation and Cleaning, Data Science, Data Visualization, Geospatial Data, Maps & Spatial Analysis, Machine Learning, Mixed Methods, Qualitative methods, Surveys, Sampling & Interviews, Regression Analysis, Means Tests, Software Output Interpretation, Other, Excel, Git or Github, RStudio, RStudio Cloud, SAS, Tableau

Manish Kumar

Availability: By appointment only

Consulting Areas: Python, R, Javascript, C, C++, APIs, Databases & SQL, Data Manipulation and Cleaning, Digital Humanities, Software Tools, Git or Github, MATLAB, RStudio

Stephanie Andrews

Consultant
Info & Data Science MIDS

Stephanie Andrews is currently studying data science in the MIDS program, having previously majored in Social Welfare as an undergraduate at Cal. After graduating, she worked as an advocate for survivors of gender-based violence, as a public policy analyst focusing on anti-trafficking initiatives, and as a software engineer for progressive and social impact organizations. She is now conducting research with the Human Rights Center's Investigations Lab, using OSINT and data science methods to investigate human rights violations.

Kurt Soncco Sinchi

Consultant
Civil Engineering

First generation student and looking to improve and apply Data Science core concepts into social impactful projects, as well as trying to leverage the information from previous cases for better insights of society. Focused on infrastructure and its impact under natural disasters.

Pratik Sachdeva, Ph.D.

Data/Research Scientist, Senior Consultant, and Senior Instructor

I am staff at the Social Sciences D-Lab. I received my Ph.D. in the Physics department at Berkeley. My research lies in the realm of theoretical/computational neuroscience, which aims to use mathematical and computational tools to better understand how neural systems operate and process information. My projects include using information-theoretic techniques to study how neural variability impacts information processing in neural circuits and investigating the statistical issues that impede the interpretation of parametric models of neural activity.

Beyond research, I'm
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Seyi Olojo

Instructor, Researcher
School of Information

Seyi is a PhD Student in the School of Information and is a member of the Algorithmic Fairness and Opacity Group. Her research broadly explores the problem space of digital memory, specifically the social discourse surrounding algorithms, ethics, and engagement. Additionally, her work often explores histories of quantification and the politics of categories within emerging technologies. She uses a mixed methods approach to research; this includes ethnography, interviews, grounded theory, surveys, data analysis and values-based design. Here at the D-lab, she leads the qualitative...

Nikita Samarin

Instructor
Electrical Engineering and Computer Science (EECS)

Nikita Samarin is a doctoral student in Computer Science in the Department of Electrical Engineering and Computer Sciences (EECS) at the University of California, Berkeley advised by Serge Egelman and David Wagner. His research focuses on computer security and privacy from an interdisciplinary perspective, combining approaches from human-computer interaction, behavioral sciences, and legal studies. Samarin is a member of the Berkeley Lab for Usable and Experimental Security (BLUES) and an affiliated graduate researcher at the Center for Long-Term Cybersecurity (CLTC) and the...

Sohail Khan

Data Science Fellow 2024-2025
School of Information

Hey everyone, I’m Sohail - a 1st years Master’s student studying Data Science at the I-School. I am interested in the intersection between Computer Science, Data Science, and Cognitive Psychology and using these tools to understand, discover, and drive the development of assistive technologies.

I have experience building with brain computer Interfaces, developing distributed data processing applications, and am currently working on a large scale archival project aimed at preserving the history and memory of resistance movements through an embedding based...

Nanqin Ying

Data Science Fellow 2024-2025
Goldman School of Public Policy

Nanqin Ying, a second-year graduate student at the Goldman School of Public Policy specializing in Development Practices, combines a robust nonprofit background with advanced data science techniques. She focuses on leveraging machine learning and big data to drive significant social change, aiming to transform insights into actionable, positive impacts on communities.