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                                             A Joint Seminar of

                 Department of Systems Engineering and Engineering Management

                                                        And

                        Department of Decision Sciences and Managerial Economics

                            The Chinese University of Hong Kong

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Date: 4:30pm to 5:30pm, April 6, 2017 (Thursday)

 

Title: Efficient advert assignment

 

Speaker:  Prof. Frank Kelly, Professor of the Mathematics of Systems, the University of Cambridge

 

Abstract:

 

In current Ad-auctions, there is an information asymmetry between the platform and advertisers: the platform typically knows more than an advertiser about the search being conducted, such as information about the searcher. Hence the platform can potentially choose prices and an allocation that depends on the platform's additional information. In contrast, the advertiser has to rely on more coarse-grained information, perhaps just the search terms of a query together with a crude categorization of the searcher.

 

We show that the information asymmetry can be used to develop a simple mechanism for advert assignment and pricing that incentivizes truthful bidding and encourages convergence to a unique Nash equilibrium that is socially optimal.

 

This is a joint work with Peter Key and Neil Walton.

 

Biography:

 

Frank Kelly is Professor of the Mathematics of Systems in the University of Cambridge. He was elected a Fellow of the Royal Society in 1989, and a Foreign Member of the National Academy of Engineering in 2012. In 2013 he was awarded a CBE for services to mathematical sciences. His main research interests are in random processes, networks and optimization. He is especially interested in applications to the design and control of networks and to the understanding of self-regulation in large-scale systems.

 

Frank Kelly has received several prizes for his work. In 1979 he won the Davidson Prize of the University of Cambridge. In 1989 he was awarded the Guy Medal in Silver of the Royal Statistical Society. He was awarded the 1991 Lanchester Prize of the Institute for Operations Research and the Management Sciences, and in 1997 the Naylor Prize of the London Mathematical Society. In 2005 he received the IEEE Koji Kobayashi Computers and Communications Award, in 2008 the John von Neumann Theory Prize of INFORMS, in 2009 the SIGMETRICS Achievement Award and the Gold Medal of the Association of European Operational Research Societies, in 2011 the Beale Medal of the Operational Research Society, in 2013 the INFORMS Saul Gass Expository Writing Award and in 2015 the Alexander Graham Bell Medal of the IEEE and the David Crighton Medal of the LMS and the IMA. He has been awarded Honorary Doctorates by Heriot-Watt University, Eindhoven University of Technology and Imperial College, London.

 

He served as Director of the Statistical Laboratory in the University of Cambridge from 1991 to 1993. He has served on the Scientific Board of HP's Basic Research Institute in Mathematical Sciences, the Scientific Council of EURANDOM, the Conseil Scientifique of France Telecom, and the Council of the Royal Society. He has chaired the Advisory Board of the Royal Institution/University of Cambridge Mathematics Enrichment Project, and the Management Committee of the Isaac Newton Institute for Mathematical Sciences.

 

He spent the academic year 2001-2 as a visiting professor at Stanford University. From 2003 to 2006 he served as Chief Scientific Adviser to the United Kingdom's Department for Transport. He was chair of the Council for the Mathematical Sciences from 2010 to 2013, a member of the RAND Europe Council of Advisors from 2008 to 2015, and Master of Christ's College from 2006 to 2016.

 

This seminar is hosted by Prof. Chen, Nan.

 

Everyone is welcome to attend the talk!

 

 

 

Venue: Room 513,

      William M.W. Mong Engineering Building (ERB),

      The Chinese University of Hong Kong.

 

SEEM-5202 Website: http://seminar.se.cuhk.edu.hk

Email: seem5202@se.cuhk.edu.hk