Dr. Jun Wang
Programme Director of MSc/MRes Web Science and Big Data Analytics
Department of Computer Science
University College London
Co-founder, MediaGamma, a spin-out from our research on online advertising
My research focus is on the areas of information retrieval, personalisation and computational advertising; current research covers both theoretical and practical aspects:
- statistical modeling of information retrieval, and dynamic information retrieval,
- data mining and collaborative filtering (recommendation),
- web economy and online advertising.
- Editor Board, Springer Journal of Big Data
- PC, the annual meeting of the Association for Computational Linguistics (ACL), 2013
- Senior PC ACM CIKM 2011, 2012, 2013
- PC ACM WSDM 2013
- PC ACM Recommender Systems 2009 2010 2011 2012 2013
- PC ACM SIGIR 2007, 2008, 2009, 2010, 2011, 2012, 2013
- CIKM 2011 Tutorial: Statistical Information Retrieval Modelling: From Probability Ranking Principle to recent advances in diversity, Portfolio Theory, and beyond
- Co-organizer: DiveRS 2011 – International Workshop on Novelty and Diversity in Recommender Systems
- ECIR2011 Tutorial: Risk Management in Information Retrieval
- Co-organizer: DDR-2011: Diversity in Document Retrieval
- Editorial Board Member of ACM SIGMM Records, 2008 -2010
- Co-organizer: International workshop: Complex Networks meet Information & Knowledge Management(CNIKM) 2009
- Best Paper Prize, ECIR2012
- Best Paper Prize, ECIR2009
- “Beyond Search – Semantic Computing and Internet Economics“, Microsoft 2007
- Best Doctoral Consortium award, ACM SIGIR06
Jun Wang is Reader in University College London and Founding Director of MSc/MRes Web Science and Big Data Analytics. His main research interests are in the areas of information retrieval, data mining and online advertising. His research has been dedicated to building an Intelligent (text and non-textual media) System that can access, retrieve, change and design the media content and its representation in such a way that it is adapted to the environment and context, and suitable for an individual person. To achieve the goal, Dr. Wang has studied statistical modelling of information retrieval, social “the wisdom of crowds” approaches for content understanding and access (collaborative filtering (recommendation)), peer-to-peer information retrieval and filtering, and, multimedia content analysis. Recently, he has developed an interest in “Web Economy” where he intends to unify information retrieval and economic models for Web ecosystems.
Dr. Wang has published over 50 research papers in leading journals and conference proceedings including ACM Trans.on Information Systems, IEEE Trans. on Multimedia, ACM Multimedia System Journal, ACM SIGIR, CIKM, SIGMM, and WWW. He was a recipient of the Beyond Search – Semantic Computing and Internet Economics award sponsored by Microsoft Research, USA in 2007; he also received the Best Doctoral Consortium award in ACM SIGIR06 for his work on collaborative filtering, the Best Paper Prize in ECIR09 for his work on applying Modern Portfolio Theory of Finance (Mean-variance Analysis) to document ranking in Information Retrieval, and the Best Paper Prize in ECIR12 for top-k retrieval modelling.
Dr. Wang obtained his PhD degree in Delft University of Technology, the Netherlands; MSc degree in National University of Singapore, Singapore; and Bachelor degree in Southeast University, Nanjing, China.