R

Andrea Lukas

UTech
Computer Science
Data Science

Hi everyone! I'm Andrea Lukas, a 3rd-year student majoring in Computer Science and Data Science at UC Berkeley. I'm passionate about UI/UX design and AI-centered human-computer interaction, and I'm actively involved in Computational Cognition research using Large Language Models (LLMs). As the Manager at D-Lab, I'm excited to contribute to the team by optimizing operations and fostering collaboration.

Outside of my academic and professional work, I’m an active member of Berkeley's Dance Community, where I participate in various teams. I also enjoy discovering new matcha spots and...

Lauren Chambers

Consultant
School of Information

Lauren Chambers is a Ph.D. student at the Berkeley School of Information, where she studies the intersection of data, technology, and sociopolitical advocacy with Prof. Deirdre Mulligan. Previously Lauren was the staff technologist at the ACLU of Massachusetts, where she explored government data in order to inform citizens and lawmakers about the effects of legislation and political leadership on our civil liberties. Lauren received her Bachelor's from Yale in 2017, where she double-majored in astrophysics and African American studies, and she spent two years after graduation in...

Nimita Gaggar

Consultant
Public Health

Passionate and driven Public Health graduate student at UC Berkeley with a strong background in program management and a relentless pursuit of excellence. I have 5+ years of experience in program management and operations in the healthcare industry. My academic journey at UC Berkeley has equipped me with a multifaceted skill set, blending strategic thinking, data-driven decision-making, and effective communication. I thrive in fast-paced, dynamic environments and have a proven ability to lead cross-functional teams toward project success.

Nicolas Nunez-Sahr

Consultant
Statistics

I lived in Santiago, Chile until I graduated from high school, and then moved to the US for undergrad at Stanford, where I obtained a Bachelor’s degree from the Statistics Department. I then worked as a Data Scientist in an NLP startup that was based in Bend, OR, which analyzed news articles. I love playing soccer, volleyball, table tennis, flute, guitar, latin music, and meeting new people. I want to get better at mountain biking, whitewater kayaking, chess and computer vision. I find nature astounding, and love finding sources of inspiration.

Ini Umosen

Consultant
Economics

Ini is a PhD candidate in the Department of Economics. She studies topics in labor economics and the economics of education using applied econometrics methods. Current work in progress includes evaluating the impact of school choice systems and investigating gender and racial bias on gig platforms. She is a former Graduate Research Fellow at the California Policy Lab. She has also been a tutor for econometrics, labor economics, and macroeconomics.

Why Data Disaggregation Matters: Exploring the Diversity of Asian American Economic Outcomes Using Public Use Microdata Sample (PUMS) Data

February 11, 2025
Taesoo Song
by Taesoo Song. Asian Americans are often overlooked in discussions of racial inequality due to their high average socioeconomic attainment. Many academic and policy researchers treat Asians as a single racial category in their analysis. However, this broad categorization can mask significant within-group disparities, leaving many disadvantaged individuals without access to vital resources and policy support. Song emphasizes the importance of data disaggregation in revealing Asian American inequalities, particularly in areas like income and homeownership, and demonstrates how breaking down these categories can lead to more targeted and effective policy solutions.

R Geospatial Fundamentals: Parts 1-2

February 25, 2025, 2:00pm
In this 2-part workshop series, we will provide an introduction to spatial analyses in R. We discuss the benefits of the additional ‘location' component that defines spatial data and how spatial data frames organize this information. Using the sf (simple features) and terra packages, we'll navigate fundamental operations for reading, writing, manipulating, and visualizing spatial data.

R Copilot Assisted Coding Workshop

February 4, 2025, 10:00am
This workshop provides a beginner-friendly introduction to coding with GitHub Copilot, a popular AI coding assistant. We will start from the basics so you can take advantage of AI assistants to improve your coding and avoid common pitfalls. First, we’ll cover how to install and set-up Visual Studio Code, a free code editor through which we will use GitHub Copilot. Then, we will go through the different features of GitHub Copilot and how to use them to help us code in R.

Finley Golightly

IT Support & Helpdesk Supervisor
Applied Mathematics

Finley joined D-Lab as full-time staff launching their career in Data Science after graduating with a Bachelor's degree in Applied Math from UC Berkeley.

They have been with D-Lab since Fall 2020, formerly as part of the UTech Management team before joining as full-time staff in Fall 2023. They love the learning environment of D-Lab and their favorite part of the job is their co-workers! In their free time, they enjoy reading, boxing, listening to music, and playing Dungeons & Dragons. Feel free to stop by the front desk to ask them any questions or...

R Fundamentals: Parts 1-4

May 5, 2025, 10:00am
This workshop is a four-part introductory series that will teach you R from scratch with clear introductions, concise examples, and support documents. You will learn how to download and install the open-sourced R Studio software, understand data and basic manipulations, import and subset data, explore and visualize data, and understand the basics of automation in the form of loops and functions. After completion of this workshop you will have a foundational understanding to create, organize, and utilize workflows for your personal research.