Data Science

D-Lab AI and Data Science Curriculum Fellowship!

August 1, 2025, 10:00am
D-Lab is looking for students to help design and develop hands-on workshops in AI and data science this summer. As a curriculum fellow, you’ll collaborate with our team to create engaging, accessible content that introduces key tools and concepts to a broad audience. This is an excellent opportunity to build your teaching portfolio, deepen your technical skills, and contribute to D-Lab’s public mission. The summer fellowship comes with a stipend of $1100. Fellows typically work independently over a few weeks, with support and feedback from D-Lab staff. We'd love to hear from you if you're interested in education, technology, or the social impact of AI. - Collaborate on cutting-edge curriculum - Flexible - $1100 fellowship Apply now or reach out to learn more!

Decision-Making Under Pressure during My PhD: Lessons from whale songs and ocean noise

May 6, 2025
by Jaewon Saw. This blog post shares a story from a field experiment using Distributed Acoustic Sensing (DAS) to detect whale vocalizations in Monterey Bay. Most of the data got overwhelmed by noise from boat engines, wave motion, and cable instability. On the final day, a spur-of-the-moment decision to add loops to the fiber optic cable dramatically improved signal quality.

Info Session: D-Lab Data Science & AI Fellowship (2025-2026)

April 17, 2025, 3:00pm
The D-Lab is seeking applications for the 2025-2026 cohort of Data Science & AI Fellows. This info session will give you an in-depth look at the D-Lab DSAI Fellowship and an opportunity for you to ask questions about the program that may be helpful to your application process to become a Fellow!

More D-Lab events and workshops coming soon!

August 1, 2025, 9:00am

More workshops coming soon...

Please subscribe to the D-Lab weekly newsletter to be notified when new workshops are available for registration.

Predicting the Future: Harnessing the Power of Probabilistic Judgements Through Forecasting Tournaments

April 29, 2025
by Christian Caballero. From the threat of nuclear war to rogue superintelligent AI to future pandemics and climate catastrophes, the world faces risks that are both urgent and deeply uncertain. These risks are where traditional data-driven models fall short—there’s often no historical precedent, no baseline data, and no clear way to simulate a future world. In cases like this, how can we anticipate the future? Forecasting tournaments offer one answer, harnessing the wisdom of crowds to generate probabilistic estimates of uncertain future events. By incentivizing accuracy through structured competition and deliberation, these tournaments have produced aggregate predictions of future events that outperform well-calibrated statistical models and teams of experts. As they continue to develop and expand into more domains, they also raise urgent questions about bias, access, and whose knowledge gets to shape our collective sensemaking of the future.

Python Fundamentals: Parts 1-4

May 5, 2025, 12:00pm
This four-part interactive workshop series is your complete introduction to programming Python for people with little or no previous programming experience. 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.

Yiyi He

Data Science Fellow 2021-2022
Landscape Architecture & Environmental Planning

Yiyi He is a Ph.D. candidate from the College of Environmental Design at University of California, Berkeley. She received her bachelor’s degree in City and Regional Planning from Nanjing University and her master’s degree in Environmental Planning from UC Berkeley. She is currently working as an AI Resident at GoogleX. Prior to this, she worked as a consultant for the Global Facility for Disaster Reduction and Recovery at the World Bank and a researcher for the Center for Catastrophic Risk Management and Federal Aviation Administration Consortium in Aviation Operations Research. Her...

Frances Leung

Data Science Fellow 2021-2022
School of Information

Frances Leung is a master’s student at UC Berkeley School of Information where she focuses her studies in information and data science. She has a keen interest in leveraging data-driven insights to better understand consumer behaviors and the world around us. In her professional work as a management consultant, she advises retailers and consumer businesses on digital transformation and creating web/mobile experiences that delight consumers through a human-centered approach. Frances holds a Master in Business Administration from York University, Schulich School...

Enrique Valencia López

Data Science Fellow 2022-2023
Graduate School of Education

Enrique Valencia López is a PhD student in the Policy, Politics and Leadership cluster at the Graduate School of Education.His research interests relate to three broad areas: the stratification of education by gender, immigration status and ethnicity; the measurement of teacher working conditions and well-being; and education in Latin America.

Before coming to Berkeley, Enrique worked for Mexico’s National Institute for Educational Evaluation and Assessment (INEE) in both the Policy and Indicators area. During that time, he co-authored Mexico’s first report on the educational...

Sahiba Chopra

Data Science Fellow 2024-2025
Haas School of Business

I'm a PhD student in the Management and Organizations (Macro) group at Berkeley Haas. I have a diverse professional background, primarily as a data scientist across numerous industries, including fintech, cleantech, and media. I hold a BA in Economics from the University of Maryland, an MS in Applied Economics from the University of San Francisco, and an MS in Business Administration from UC Berkeley.

My research focuses on the intersection of inequality, technology, and the labor market. I am particularly interested in understanding how to reduce inequality in...