July 17, 2019, 14:00, Room GC B1 10 (click here for the map)
How should Uber set its prices and allocate its drivers? There are two separate types of modelling that are needed. First, we need to model how users make choices and how their choices depend on price; this is the field of discrete choice modelling, a staple of transport modelling. Second, we need to model traffic flows and how capacity should be allocated in a network; this is the field of network utility maximization, pioneered by Frank Kelly in the context of Internet congestion control. I will describe how these can be linked, via a surprising application of Shannon's information theory. I will also suggest avenues of research on how machine learning models of human behaviour might be integrated with models of urban or economic systems. Pictures: https://www.cl.cam.ac.uk/~djw1005/AboutMe/damon__bigsur.jpg
Damon Wischik is a lecturer in the Computer Science department at Cambridge University, and a fellow of the Alan Turing Institute. He specializes in data science and machine learning. He spent five years as chief data scientist at Urban Engines, a startup which worked on urban analytics and behaviour nudging. Before that, he was a researcher in probability theory, computer networking, and statistics, in maths at Cambridge University and in computer science at University College London.