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Friday, December 1 • 3:25pm - 3:50pm
Addressing city-scale optimization problems of ride and vehicle-sharing

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In this presentation, I will show how analyzing data of millions of NYC taxi trips led us to create a powerful network-based optimization approach for an optimal management of a fleet of vehicles serving a city's mobility demand.

avatar for Mohammed Vazifeh

Mohammed Vazifeh

Lead data scientist, MIT Senseable City Lab
Moe Vazifeh is a postdoctoral associate/lead data scientist at MIT Senseable City Lab. He is also a cofounder of a Vancouver-based startup, Q.I. Leap Analytics. His interests are centered around mining and modeling complex patterns in large-scale spatio-temporal urban data as well... Read More →

Friday December 1, 2017 3:25pm - 3:50pm