Matching Algorithms in E-Commerce

Speaker:        Pan Xu
                University of Maryland, College Park

Title:          "Matching Algorithms in E-Commerce"

Date:           Thursday, 7 March 2019

Time:           11:00am - 12 noon

Venue:          Room 4504 (via lift 25/26), HKUST

Abstract:

Matching is a fundamental model in combinatorial optimization. During the
last decade, stochastic versions of matching models have seen broad
applications in various matching markets emerging in E-Commerce. In this
talk, I will first present two basic matching models, namely offline and
online stochastic matching, and related fundamental algorithmic
frameworks. Then I will survey new challenges and our corresponding
algorithmic solutions when we apply matching models to different real
matching markets, including crowdsourcing marketplaces (e.g., Amazon
Mechanical Turk), ridesharing platforms (e.g., Uber and Lyft), online
food-ordering platforms (e.g., Grubhub), and online recommendation systems
(e.g., Amazon recommendations).


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Biography:

Pan Xu is currently a Ph.D. student in the Department of Computer Science
at the University of Maryland (UMD), College Park. He is very fortunate to
be supervised by Dr. John Dickerson and Dr. Aravind Srinivasan.

Pan's research interests broadly span the intersection of Algorithms,
Operations Research, and Artificial Intelligence. Recently, he focuses on
the design of efficient algorithms for offline and online matching models
and their applications in various real matching markets, including
crowdsourcing marketplaces, ridesharing platforms, and online
recommendation systems. He has been fortunate to be supported by several
Fellowships and Awards including an F. Wendell Miller Fellowship
(2009-2012, ISU), a Research Excellence Award (2013, ISU), an Ann G. Wylie
Dissertation Fellowship (2018-2019, UMD) and an Outstanding Graduate
Assistant Award (2018, UMD). He is the single nominee by the CS Department
at UMD for the CMNS Board of Visitors Outstanding Graduate Student Award,
2018.