Qiang Yang

 
Qiang Yang

New Bright  Professor of Engineering, Chair Professor and
Head of Department of Computer Science and Engineering,
Hong Kong University of Science and Technology


IEEE TBD
   


http://ijcai-15.org


IEEE TBD Submission Link

IJCAI 2015 Proceedings

 

Address:

Clearwater Bay, Kowloon, Hong Kong, qyang (at) cse (dot) ust (dot) hk, Phone: (00852) 2358-7009, Fax: (00852) 2358-2679

Research Interests:

  • Artificial Intelligence: Transfer Learning, Machine Learning, Planning, Data Mining

Online Publication List | Google Scholar | Transfer Learning Survey, Software and Data Resources
Transfer Learning in Social Recommendations | MIT Technology Review Article (ViCAD System)
Transfer Learning Papers in Recent Conferences (Link) | Book: Crafting Your Research Future, Morgan&Claypool Publishers (link) (PDF) | Hong Kong RGC Research Frontiers Article: Heterogeneous Transfer Learning  Eng, Chn | Bio

** Chair, IJCAI-2017 Awards Committee:  Call for Award Nominations

** Chair,  ACM KDD 2017 Test of Time Award CommitteeCall for Award Nominations

** Chair, IEEE Intelligent Systems Top-10-to-Watch Committee: Call for Award Nominations

    Positions and Education:

    • 2015 - present: CSE Department Head, University New Bright Professor of Engineering and Chair Professor, Hong Kong University of Science and Technology
    • 2016 - present: Director, HKUST Big Data Institute
    • 2012 - 2014, Founding Head, Huawei Noah Ark Research Lab
    • 2001- present: HKUST: Full Professor (2007 - ) Associate Department Head (PG and Research)  (2011 - 2012), Postgraduate Coordinator (2007-2009), Associate Professor, 2001-2007,  Founding Co-Director of RMBI Program HKUST (2007-2011)
    • 1995 - 2001: NSERC Industry Research Chair (1995-2001), Associate/Full Professor at Simon Fraser University, BC Canada (1995 - 2001)
    • 1989 - 1995:  Assistant/Associate Professor, Computer Science, University of Waterloo, Waterloo, Ont. Canada 
    • 1999 - 2000: Visiting Researcher at Microsoft Research China and University of Washington, USA
    • Laboratory Affiliations: AI and Databases

    Honor:

      • AAAI Fellow (2013 - ) Association for the Advancement of Artificial Intellignece
        • for significant contributions to AI Planning, Data Mining and Case-based Reasoning
      • AAAS Fellow (2012 - ) American Association for the Advancement of Science
        • for significant contributions to Data Mining, Learning and Planning: theory, applications, and services 
      • IAPR Fellow (2012 -) International Association of Pattern Recognition
        • for significant contributions to Data Mining and Transfer Learning
      • IEEE Fellow (2009 - ) Institute of Electrical and Electronics Engineers
        • for Significant Contributions to the Understanding and Application of Intelligent Planning, Learning and Data Mining
      • ACM Distinguished Scientist (2011 - ) Association of Computing Machinery, Link to ACM

    Awards: