Spring 2022 EconCS Seminars

Spring 2022

The EconCS Group holds an Economics and Computer Science research seminar each semester.

Spring 2022 meetings are held at 1 - 2:30 PM on Fridays. Seminar Coordinators for Spring '22 are Srivatsa R Sai and Daniel Halpern.

Visit us soon for our upcoming Spring 2022 seminar events!

 

2022 Jun 03

Uber's Driver-Side Surge Pricing: Background, Motivation, and Execution

1:00pm to 2:30pm

Location: 

SEC 1.413 & on Zoom here: https://harvard.zoom.us/j/97692964231?pwd=K05BMEhDNTZtbUhHYkZ5S21qZ2FKQT09#success

Calvin Li, formerly at Uber and the main architect behind their current surge pricing strategies. It will occur at the usual place and the usual time: this Friday, 6/3, at 1 pm ET, in SEC 1.413 and streamed on zoom ...

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2022 Apr 01

Automated Market Design via Reinforcement Learning

1:00pm to 2:30pm

Location: 

SEC 1.413 & on Zoom here: https://harvard.zoom.us/j/97692964231?pwd=K05BMEhDNTZtbUhHYkZ5S21qZ2FKQT09#success

Speaker:  Gianluca Brero

Title:  Automated Market Design via Reinforcement Learning

Abstract:  In this talk, I will introduce the use of reinforcement learning to design algorithmic markets. First, I will show how (deep) reinforcement learning algorithms can be used to design sequential price mechanisms, where we can assume truthful agents’ behavior. I will then consider the more general class of mechanisms that combine a messaging round with a sequential-pricing... Read more about Automated Market Design via Reinforcement Learning
2022 Feb 18

The Challenge of Understanding What Users Want: Inconsistent Preferences and Engagement Optimization

1:00pm

Location: 

SEC 1.413 & on Zoom here: https://harvard.zoom.us/j/97692964231?pwd=K05BMEhDNTZtbUhHYkZ5S21qZ2FKQT09#success

Presenter:  Manish Raghavan

Abstract: Online platforms routinely optimize the content they recommend to their users based on behavioral data. At its core, the use of behavioral data is predicated on a revealed preference assumption: users choose what they like; and thus what they choose reveals what they like. And yet, research has repeatedly demonstrated that behavior can be a poor proxy for users’ preferences, exactly because users themselves are conflicted. Indeed, our own intuition tells us that we often make choices in the moment that are inconsistent with our...

Read more about The Challenge of Understanding What Users Want: Inconsistent Preferences and Engagement Optimization