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Women in CS Talk: Title: Dynamics of Predictions and Decision-Making

Tijana Zrnic: Final-year PhD Candidate, Electrical Engineering and Computer Sciences, UC Berkeley

Event Details

Monday, September 26, 2022
4-5 p.m.


Abstract: Predictive models deployed in social settings are often performative. This means that the model's predictions---by means of being used to make consequential downstream decisions---influence the outcomes the model aims to predict in the first place. For example, travel time estimates influence routing decisions and thus realized travel times, stock price predictions influence trading activity and hence prices. Such feedback-loop behavior arises in a variety of domains, including public policy, trading, traffic predictions, and recommendation systems. In this talk I will discuss phenomena that arise when iteratively optimizing a predictive model in a performative context.

Bio: Tijana Zrnic is a final-year PhD student in Electrical Engineering and Computer Sciences at the University of California, Berkeley, advised by Moritz Hardt and Michael Jordan. Her PhD work explores challenges that arise when inference is performed in dynamical settings, with a particular focus on situations involving feedback loops. Previously she received a Bachelor’s degree in Electrical and Computer Engineering from the University of Novi Sad in Serbia.