Early-Stage Research in the Economics of AI and Big Data
Abhishek Nagaraj, Professor
Business, Haas School
Closed. This professor is continuing with Fall 2025 apprentices on this project; no new apprentices needed for Spring 2026.
This URAP project exposes students to one or more of the ongoing projects that the professor (Abhishek) is working on along in his Data Innovation and AI Lab (DIAL) with PhD students and other research assistants in the Berkeley-Haas School of Business.
The idea of this URAP group is to provide students with exposure to research at the frontier of research in business economics and the economics of information and business strategy. Most projects involve cleaning, processing and analyzing big data sets in a variety of different fields of relevance.
Examples of ongoing projects include:
(a) building simulations of user behavior with AI systems
(b) understanding the impact of training data on AI output
(c) unpacking contribution dynamics in open source systems
(d) understanding the impact of weather forecasts on economic activity
Please take a look at the website for the Data Innovation and AI Lab for list of students (https://www.abhishekn.com/lab/students) and more info on working with us (https://www.abhishekn.com/lab/work-with-us). The website also has examples of past projects.
You will work with Abhishek and/or one of the PhD students or Postdocs in Berkeley Haas collaborating with him. Work will be performed remotely, and we will have regular meetings to discuss your progress.
When submitting your application please include:
-- your transcript listing grades/GPA in key courses
-- a short description of the most complex data analysis project you have undertaken. Links or attachments to past work/project output is appreciated.
Role: Depending on the project, you will be involved with
(a) qualitative/archival research
(b) cleaning, processing and updating large datasets
(c) producing summary statistics, simple regression analysis
(d) working with large language model simulations and outputs
Qualifications: You should have experience handling and processing large datasets (10-100GB+) and with the linux command line. Experience fine tuning, prompting with LLMs and AI agents is also helpful.
Exposure to Python/Jupyter/R/Stata/SQL is also helpful.
Exposure to classes in econometrics, micro economics and data/science is appreciated, but not necessary.
Hours: 9-11 hrs
Related website: https://www.abhishekn.com/about-lab
Engineering, Design & Technologies Social Sciences