Evimaria Terzi is a Professor of Computer Science at Boston University. Her work focuses on algorithmic problems in team formation, recommender systems and network applications. She joined BU in 2009 after being a Research Staff Member for two years at the IBM Almaden Research Center. She got her PhD in CS from the University of Helsinki (Finland), her MSc in CS from Purdue University (USA) and her BSc also in CS from the Aristotle University (Greece). Her research is funded by NSF as well as gifts from companies such as Microsoft, Google and Yahoo.

AG 1, AG 2, AG 3, INET, AG 4, AG 5, SWS, RG1, MMCI   Info

AG Audience

English

540 Minutes

Saarbrücken

On-demand ride-hailing platforms like Uber and Lyft are helping reshape urban transportation, by enabling car owners to become drivers for hire with minimal overhead. Such platforms are a multi-sided market and offer a rich space for studies with socio-economic implications. In this talk I am going to address two questions:

1. In the absence of coordination, what is the best course of action for a self-interested driver that wants to optimize his earnings?

2. In the presence of coordination, is it possible to maximize social welfare objectives in an environment where the objectives of the participants (drivers, customers and the platform) are (often) misaligned?

We will discuss the computational problems behind these problems and describe simple algorithmic solutions that work extremely well in practice. We will demonstrate the practical strength of our approaches with well-designed experiments on novel datasets we collected from such platforms.

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Danielle Dalton

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