Early-Stage Research in the Economics of Information and Big Data Analytics
Abhishek Nagaraj, Professor
Business, Haas School
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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 Lab 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) impact of press coverage of scientific articles on their diffusion
(b) emerging technologies like the impact of generative AI and LLM systems
(c) impact of music streaming platforms in addressing gender inequality in music
(d) impact of political partisanship on scientific innovation
Please take a look at the website for the Data Innovation 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:
-- a CV or a 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
Qualifications: You should have experience handling and processing large datasets (10-100GB+) and with the linux command line.
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