Python

Caedi Seim

Discovery Consultant, UTech
Data Science Discovery Program

Hello! I'm Caedi and I'm a junior studying Data Science with a domain emphasis in Cognition. I'm interested in leveraging data science for non-technical fields, closing the data literacy gap, and I'm also very interested in design. Always willing to chat!

Daniel Lobo

Computational Social Science Fellow
Sociology

Daniel Lobo is a PhD student in the Department of Sociology with an emphasis in Political Economy at UC Berkeley. He is broadly interested in how culture, or the unspoken “rules of the game,” reproduces inequality within a system of racial capitalism. At the individual level, he is interested in documenting and measuring the extent to which cultural capital and social capital enable or constrain opportunities for intergenerational mobility. At the organizational level, he is interested in documenting and measuring the extent to which culturally-based selection and promotion processes...

Understanding Rock Climbing using Python & SQL

March 22, 2022
Understanding Rock Climbing using Python & SQL

The Rise of Climbing

As an avid rock climber, I’ve been curious about how climbing became so popular in such a brief time, and what these climbers look like. Unlike other well established sports such as tennis, football, or basketball, climbing has only recently gained attention on the public stage, and little data is available about this burgeoning sport.For context, back in the day, climbing was a serious commitment! You had to find a buddy to learn how to use climbing equipment...

Twitter Text Analysis: A Friendly Introduction

October 25, 2022

Read part 2 here.

Introduction

Text analysis techniques, including sentiment analysis, topic modeling, and named entity recognition, have been increasingly used to probe patterns in a variety of text-based documents, such as books, social media posts, and others. This blog post introduces Twitter text analysis, but is not intended to cover all of the aforementioned topics. The tutorial is broken down into two parts. In this very first post, I...

Peter Amerkhanian

Graduate Student Researcher (GSR), Instructor
Goldman School of Public Policy (GSPP)

I’m a D-Lab GSR and a graduate student in The Goldman School’s Master of Public Policy/The I School’s Graduate Certificate in Applied Data Science. I have 5 years of experience working on data problems in government and nonprofits. I’m interested in social policy, program evaluation, and computational methods. Python is my principal language, but I’ve developed experience using and teaching a variety of other tools, including R, Excel, Tableau, and JavaScript. I deeply enjoy teaching data science methods and am excited to be a part of the D-Lab.

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

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...

Bo Yun Park, Ph.D.

Postdoc
D-Lab

I am a Postdoctoral Scholar in the D-Lab at the University of California, Berkeley. My research lies at the intersection of political, cultural, and transnational sociology. I am particularly interested in dynamics of social inclusion and exclusion, social change, technology, and digital politics. My dissertation investigated how political strategists in France and the United States craft narratives of political leadership for presidential candidates in the digital age. I received my Ph.D. in Sociology at Harvard University, where I was affiliated with the Institute for Quantitative Social...

Avery Richards

Senior Data Science Fellow
School of Public Health

Avery is an MPH graduate at the School of Public Health. With a background in literature and behavioral health, his current research focuses on innovations in applied epidemiology, including multidisciplinary approaches to health and social science data. Avery's general interests include public health surveillance, data quality assurance, and geospatial analysis.

Shivani Patel

IUSE Undergraduate Advisory Board
Cognitive Science
Data Science

Hi! I’m a third-year at UC Berkeley studying Cognitive Science and minoring in Data Science. I will be pursuing a Doctorate of Physical Therapy with an emphasis in Sports Medicine but will be using my Data Science education as a way to enhance the field. I like learning about business models, impacted industries, and approaches to solving major problems in our world/communities.