Evimaria Terzi

"Simple models for optimizing driver earnings in the ride-sharing platforms"

( MPI-SWS talk in Kooperation mit dem Fachbereich Informatik)

On-demand ride-hailing platforms like Uber and Lyft are helping reshape urban transportation, by enabling carowners to become drivers for hire with minimal overhead. Such platforms are a multi-sided market and offer a rich spacefor 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 optimizehis earnings?2. In the presence of coordination, is it possible to maximize social welfare objectives in an environment where theobjectives 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 workextremely well in practice. We will demonstrate the practical strength of our approaches with well-designed experimentson novel datasets we collected from such platforms.

Bio: Evimaria Terzi is a Professor of Computer Science at Boston University. Her work focuses on algorithmic problemsin team formation, recommender systems and network applications. She joined BU in 2009 after being a Research StaffMember 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.

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