Promoting Pro-social Behavior through End-to-End Data Science
Presenter
Doctoral Candidate at the School of Information
Time and location
North Quad 4330, Thursday (1:00-2:00) pm
Abstract
In this talk, I introduce how I employ end-to-end data science to promote behavioral change for pro-social benefits. More specifically, I conduct data analysis with causal awareness; 2) design recommender systems for individual actions and 3) implement field experiments to change user behavior. I will present their applications to increase user participation in microfinance and sharing economies.
Short Bio
Wei Ai is a Ph.D. candidate in the University of Michigan School of Information, advised by Qiaozhu Mei. His research interest lies in data science for social good, where the advances of machine learning and data analysis algorithms translate into great impacts on society. He holds a B.S. in Computer Science and a B.A. in Economics from Peking University in China. His research has been published in top journals and conferences, including PNAS, ACM TOIS, WWW, and ICWSM.