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Sessions run Wednesdays from 4:30–5:30 PM in CoDa E160. Each session features a different Stanford speaker; talk titles are announced by the organizers.

Sessions run Wednesdays from 4:30–5:30 PM in CoDa E160. Each session features a different Stanford speaker; talk titles are announced by the organizers.
A eureka moment is a two-step process: discovering something new and surprising, and establishing that it is correct. Drawing on her work at Axiom, Carina will discuss the transition from solving mathematical benchmarks to contributing to research, and from proving individual theorems to formalizing mathematical theories in Lean.

A eureka moment is a two-step process: discovering something new and surprising, and establishing that it is correct. Drawing on her work at Axiom, Carina will discuss the transition from solving mathematical benchmarks to contributing to research, and from proving individual theorems to formalizing mathematical theories in Lean.
Speaker: Hannah Li, Assistant Professor, Columbia Business School
Presentation title: The Interplay of User Behavior and Algorithm Design in Digital Ecosystems
Abstract: The interactions between user behavior and algorithms employed on online platforms present challenges that conventional data science tools like A/B testing and recommender systems often overlook. For example, recommender systems can create feedback loops that affect both user and content creator retention. Moreover, users may strategically engage with or avoid certain content to shape their future recommendations. This talk highlights several ways these dynamics can influence platform learning and outcomes and suggests modifications to mitigate these challenges.
Logistics details for each session will be provided to registered participants. Sign up here to be included on the mailing list and learn about future events.
This talk is co-sponsored by USF's Master's in Applied Economics and the Stanford Causal Science Center. For additional information and abstracts from past talks, please click here