Phone : +33 (0)4 76 61 50 71 Onno.Zoeter@xrce.xerox.com
Keywords: (Bayesian) Machine Learning, Mechanism Design, Approximate Inference Demand Management, Transportation.
I am interested in constructing systems that take optimal actions in an environment that is driven by random events and intentional actions of self-interested agents. In particular I am intrigued by the following observation: Learning models of human behaviour and using them to rank, filter, assign, etc. are fundamentally different problems from their analogues in say biology and medicine: humans will be aware of their impact on the system and adapt their behaviour.
When applying machine learning approaches to human data sources we need to take into account incentives. Recent results from the fields of mechanism design, Bayesian statistics and optimal control allow us to do so.
There are a surprising number of important applications in recent e-commerce and big data trends that have the property that a central system needs to learn and coordinate among strategic agents. Examples of applications I have worked on include on-line advertisement selection, outsourcing, worker quality tracking and selection, and demand management for transportation. Since 2010 I have been leading a team of researchers who work on this last topic and this takes most of my time.
Demand management, the combination of demand based pricing and smart information provisioning systems, has in recent years found several first-of-its-kind applications, with cordon pricing in London, time differentiated tolling in Sweden and Singapore, and demand based parking rates in LA. The principles for these projects go back at least to papers William Vickrey published in the 1950's. He made the argument that public utilities such as highways, parking spaces, and public transport, should not be accessible for free, even though they are paid for by general tax money. Giving free access leads to congestion and general inefficient use: people that with little inconvenience can avoid peak hours and peak locations, have not enough incentives to do so. People familiar with Vickrey's second price auction will find it interesting to know that the development of the two ideas occurred pretty much at the same time, and in both the second price auction and demand management the fundamental principle is to let strategic agents pay the externality they impose on society to ensure the most efficient use of scarce resources.
Our team develops Vickrey's ideas further and makes them ready for practical deployment. We design and implement demand based pricing algorithms, study patterns in data obtained from on-street sensors and develop methods to communicate the changes in rates. Our work is in active use in Los Angeles for on-street parking (www.laexpresspark.org). The project was referred to in the MIT Technology Review when it selected Xerox among the 50 most disruptive companies in 2013, was awarded the OECD International Transport Forum's 2014 Promising Innovation in Transport Award, and the 2014 International Parking Institute's Award of Excellence.
In 2014 Fortune magazine selected me among their 20 Big Data All-Stars.
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