Programming Languages

James Hall

Consultant
Department of Statistics

James Hall is a graduate student in the Statistics MA program at University of California, Berkeley. He is a husband and father to three awesome kids. Originally from Baltimore, MD, James earned his bachelors in Mathematics at the United States Military Academy at West Point, NY in 2011, and served as a U.S. Army officer. He’s served as a leader at multiple levels within large organizations with a professional focus on visualizing and communicating complex analysis to decision makers. James’ experience and coursework give him expertise in navigating different statistical methods,...

Hikari Murayama

Senior Data Science Fellow, Senior Instructor
Digital Health Social Justice
Energy and Resources Group

Hikari is a graduate student in the Energy and Resource Group. Her research interests involve utilizing remote sensing and geospatial analysis to address pressing problems at the intersection of humans and climate. She recently served as a Data Science for Social Good Fellow at the University of Washington eScience Institute in the summer of 2020. She is experienced and happy to help in the areas of geospatial analysis, remote sensing, and other statistical analyses and methods. Hikari is devoted to helping community members realize their potential to conduct...

Cheng Ren

Senior Data Science Fellow
School of Social Welfare

Cheng Ren is a D-Lab Senior Data Science Fellow and a Ph.D. student at the School of Social Welfare. His research interests are community engagement and assessment, nonprofit development, community database, computational social welfare, and data for social goods.

Aniket Kesari, Ph.D.

Former D-Lab Postdoc and Senior Data Science Fellow
Berkeley Law

Aniket Kesari was a postdoc and data science fellow at D-Lab. He is currently a research fellow at NYU’s Information Law Institute, and will join the faculty of Fordham Law School in 2023. His research focuses on law and data science, with particular interests in privacy, cybersecurity, and consumer protection.

Featured D-Lab Blog Post: Introducing “A Three-Step Guide to Training Computational Social Science Ph.D. Students for...

Reduce, Reuse, Recycle: Practical strategies for working with large datasets

October 12, 2022
Angela Liu

When the size of your datasets start to approach the size of your computer’s available memory, even the simplest data wrangling tasks can become frustrating. Suddenly, reading in a .csv or calculating a simple average becomes time-consuming or impossible. As students or researchers, accessing additional computing resources can be costly or is not always an available option. Here are some principles and strategies for reducing the overhead of your dataset while keeping the momentum going. The code mainly focuses on reading csv files - a very common data format - into Python...

Christopher Paciorek, Ph.D.

Research Computing Consultant, Adjunct Professor
Department of Statistics
Research IT

Chris Paciorek is an adjunct professor in the Department of Statistics, as well as the Statistical Computing Consultant in the Department's Statistical Computing Facility (SCF) and in the Econometrics Laboratory (EML) of the Economics Department. He is also a user support consultant for Berkeley Research Computing. He teaches and presents workshops on statistical computing topics, with a focus on R.

Swetha Pola

Research Fellow
School of Information

Swetha (she/her) is a 5th Year Master of Information and Data Science student at the School of Information, with experience in Cognitive Science, Psychology research, and product management. Her research interests include building ethical, transparent AI and the impacts of technologies (specifically, mass media, surveillance, and algorithms of bias) on longitudinal behavioral health. She is happy to help with questions on Python, R, SQL, machine learning, neural networks, statistical analysis, and research design!

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Ash Tan

Consultant
School of Information

Ash is a Masters of Information and Data Science student at the Berkeley School of Information. He currently studies data collection, analysis, and visualization, as well as research design and machine learning techniques. His interests include cognitive science, Wikipedia data, and privacy research.

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Priscila Amorim

Changemaker Technology Project
Data Science
Digital Health Social Justice

Priscila Amorim is a recent graduate of UC Berkeley's Bachelor's of Arts in Data Science program, and is currently attending Northwestern Univerisity for a Master's of Science in Data Science. Priscila is passionate about the intersection of technology and social justice, and in particular, health justice. Their goal is to work on climate justice through database management or data engineering to support data scientists and analysts in their work through the availability of ubiquitous data. Priscila is currently working on the Changemaker's Digital Health Project to help create...

Why Teaching Social Scientists How To Code Like A Professional Is Important

September 23, 2020
Jae Yeon Kim, Ph.D.

I use data science to study political learning, organization, and mobilization among marginalized populations. I have always loved programming and want to serve people lacking voice and representation in a society. I am blessed to have found and chosen computational social science—a field situated between social science and data science—as my main research area.

I also love teaching people how to code, especially social scientists, and I take that mission seriously. I have taught computational tools and techniques at both graduate and undergraduate levels in semester-...