Data Science

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...

Teaching Data Science as a Tool for Empowerment

February 18, 2025
Elijah Mercer
by Elijah Mercer. Data literacy is a powerful tool for empowerment, especially for historically marginalized communities. Through Data Cafecito at Roadmap to Peace and helping teach Data 4AC at UC Berkeley, Elijah Mercer helps bridge the gap between data, advocacy, and justice. Data Cafecito fosters culturally responsive data practices for Latinx-serving organizations, while Data 4AC challenges students to critically analyze data’s role in systemic inequities. Drawing from his experience in education, Mercer uses interactive teaching methods to make data accessible and meaningful. By centering storytelling and community-driven insights, he aims to equip individuals with the skills to use data for social change.

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...

Sanjana Gajendran

Consultant
MIMS

I'm a second year MIMS Student with a focus on Data Science and Natural Language Processing. During the Summer 2023, I interned at Genentech as a Data Science Intern.

Thomas Lai

Consultant
School of Information

I am a Product Engineer passionate about applying engineering, data science, machine learning, and problem-solving principles to improve device performance and solve complex challenges. With experience in statistical analysis, lab bench automation, and Python scripting, I have developed a strong technical skill set that allows me to make meaningful contributions to any project. Beyond my work, I am also passionate about exploring new topics and ideas, from the latest technology trends to how to improve the overall well-being of humans. I enjoy applying the first principle to any...

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.

Gaby May Lagunes

Consultant
ESPM

Hello! I’m Gaby (she/her). I am PhD student at the ESPM department, I hold a masters in Data Science and Information from the Berkeley ISchool and I have 5+ years of industrial experience in different data roles. Before that I got a masters in Engineering for International Development and an undergraduate degree in Physics from University College London. And somewhere between all that I got married, survived the pandemic, and had two awesome boys. I’m very excited to help you use data to enhance your work and your experience here at Berkeley!

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.

Python Fundamentals: Parts 4-6

March 11, 2025, 11:30am
This three-part interactive workshop series teaches you intermediate programming Python for people with previous programming experience equivalent to our Python Fundamentals: Parts 1-3 workshop. By the end of the series, you will be able to apply your knowledge of basic principles of programming and data manipulation to a real-world social science application.

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.