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Simulating cities to minimize Uber gas usage

  • Aug 6, 2014 · 6:30 PM

Bradley Voytek, Data Evangelist at Uber and Assistant Professor at the University of California, San Diego

Uber has two main goals: 1) Get you a ride when you need it, and; 2) Make sure our driver partners are maximizing their earnings. One way of maximizing driver earnings is to minimize gas usage, which has the wonderful side benefit of reducing emissions. Here I introduce Uber’s city simulation framework and explain how and why we simulate Uber passenger/driver interactions to identify optimal behaviors for drivers to take between trips. These simulations provide Uber with a suite of testable A/B hypotheses. In other words, the city simulation framework generates possible A/B tests to optimize the Uber client experience and minimize gas usage to maximize driver partner earnings.

Brad is an Assistant Professor of Computational Cognitive Science and Neuroscience at the University of California, San Diego and Data Evangelist for the on-demand car service company, Uber, Inc. In his neuroscience life, Brad studies cognition and neural network communication using data-mining, lesion experiments, human intracranial recordings, brain-stimulation, brain-computer interfacing, and whatever other tools he can get his hands on. He co-created the meta-analytic neuroscience research aggregation tool and hypothesis generation site http://brainSCANr.com with his wife Jessica Bolger Voytek. He's an avid science teacher and outreach advocate and is the world's zombie brain expert (seriously).


RSVP list to open two weeks in advance.


SCHEDULE

• 6.30 to 7:00 pm:   light refreshments

• 7:00 to 8:00 pm:   talk

 

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