• Data Mining and Machine Learning
• Artificial Intelligence
• Data Security
• Decision Support
• Applications in E-Learning, Business, Industry, Bio-Informatics, Health Informatics, Software Engineering

• Ph.D., Computer Science (GPA: 92.5)
  The University of Western Ontario, London, Ontario, Canada August 2007
  Thesis Title: Cost-sensitive learning with data acquisition
• M.Sc., Computer Science (GPA: 4.0)
  University of New Brunswick, Fredericton, New Brunswick, Canada December 2003
  Thesis Title: Learning weighted Naive Bayes for accurate ranking
• M.Sc.E., Computer Engineering (GPA: 87.9)
  Suzhou University, Suzhou, Jiangsu, China July 1999
  Thesis Title: New algorithms of cryptology and security for computer network
• B.Sc.E., Metallurgical Engineering & Materials Science (GPA: 90.6)
  Chongqing University, Chongqing, China July 1993

• Best Paper Award Runner-Up, ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD08), 2008
• NSERC Postdoctoral Fellowship (total $80,000)
• Best Presentation Award, The University of Western Ontario Research in Computer Science Annual Conference, 2007
• Student Travel Award, ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD07), 2007
• Nominated for Graduate Teaching Assistant Award, The University of Western Ontario, 2006 - 2007
• Three CS Publications Incentive Awards, Department of Computer Science, The University of Western Ontario, 2004 - 2005, 2005 - 2006, 2006 - 2007 respectively
• Nominated for Robert and Ruth Lumsden Fellowships in Science, The University of Western Ontario, 2006
• Best Poster Award, The UW and IEEE Kitchener-Waterloo Section Joint Workshop on Knowledge and Data Mining (2006), University of Waterloo, ON, Canada
• Student Travel Award, International Conference on Machine Learning (ICML06), 2006
• Student Travel Award, American Association of Artificial Intelligence (AAAI06), 2006
• NSERC Post-graduate Scholarship (total $63,000), 2005 - 2008
• Western Graduate Research Scholarship, The University of Western Ontario, 2005 - 2008
• Special University Scholarship, The University of Western Ontario, 2004
• Graduate Scholarship, University of New Brunswick, 2002 - 2003

Articles in Peer-refereed Journals

• Ling, C.X., Sheng, V.S., & Yang, Q. (2006). Test Strategies for Cost-Sensitive Decision Trees. IEEE Transactions on Knowledge and Data Engineering, August 2006 (Vol. 18, No. 8), 1055-1067.
• Zhang, S., Qin, Z., Ling, C.X., & Sheng, S. (2005). "Missing is Useful": Missing Values in Cost-sensitive Decision Trees. IEEE Transactions on Knowledge and Data Engineering, December 2005 (Vol. 17, No. 12), 1689-1693.

Articles in Peer-refereed Conference Proceedings

• Sheng, V.S., Provost, F.J., & Ipeirotis, P.G. (2008). Get Another Label? Improving Data Quality and Data Mining Using Multiple, Noisy Labelers. Proceedings of the 14th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD08), 614-622, August 24-27, Las Vegas, Nevada, USA. (Acceptance rate: 50/~500 < 10%, Best Paper Award Runner-Up)
• Sheng, V.S., & Ling, C.X. (2007). Partial Example Acquisition in Cost-Sensitive Learning. Proceedings of the 13th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD07), 638-646, August 12-15, San Jose, California, USA. (Acceptance rate: 1/12, a top data mining conference)
• Sheng V.S., & Ling, C.X. (2007). Roulette Sampling for Cost-Sensitive Learning. Proceedings of the 18th European Conference on Machine Learning (ECML07), 724-731. September 17-21, Warsaw, Poland.
• Sheng, V.S., & Ling, C.X. (2006). Feature Value Acquisition in Testing: A Sequential Batch Test Algorithm. Proceedings of the 23rd International Conference on Machine Learning (ICML06), 809-816. June 25-29, Carnegie Mellon University in Pittsburgh, Pennsylvania. (A top machine learning conference)
• Ling, C.X., Sheng, V.S., Bruckhaus T., & Madhavji, N.H. (2006). Maximum Profit Mining and Its Application in Software Development. Proceedings of the 12th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD06), 929-934. August 20-23, Philadelphia, USA.
• Sheng, V.S., & Ling, C.X. (2006). Thresholding for Making Classifiers Cost-Sensitive. Proceedings of the 21st National Conference on Artificial Intelligence (AAAI06), 476-481. July 16-20, 2006, Boston, Massachusetts. (A top AI conference)
• Sheng, V.S., Ling, C.X., Ni, A., & Zhang, S. (2006). Cost-Sensitive Test Strategies. Proceedings of the 21st National Conference on Artificial Intelligence (AAAI06), 482-487. July 16-20, 2006, Boston, Massachusetts.

A list of his complete publications. Also find his papers listed in DBLP here and here.

PROFESSIONAL SERVICES AND ACTIVITIES

Program Committee Member

• Session chair: INFORMS Annual Meeting (data mining/machine learning session, 2008)
  
• The Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD07)
  

Reviewer reviewer for journals and book chapters

• Journal of Machine Learning
  
• IEEE Transactions on Knowledge and Data Engineering
  
• Data Mining and Knowledge Discovery
  
• ACM Transactions on Knowledge Discovery from Data
  
• International Journal of Information Technology & Decision Making
  
• Journal of Computer Science and Technology
  
• Encyclopedia of Data Warehousing and Mining - 2nd Edition, 2008
  

Reviewer/external reviewer for conferences

• International Joint Conference on Artificial Intelligence (IJCAI05, IJCAI07)
  
• International Conference on Data Mining (ICDM04, ICDM05, ICDM06, ICDM07)
  
• IEEE/WIC/ACM International Conference on Web Intelligence (WI07)
  
• IEEE International Conference on Bioinformatics and Biomedicine (BIBM07)
  
• European Conference on Principles and Practice of Knowledge Discovery in Databases (PKDD05)
  
• The Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD05, PAKDD06, PAKDD07)
  

Reviewer/external reviewer for workshops

• Utility-Based Data Mining (UBDM05, UBDM06)
  

Memberships

• ACM
  
• AIS (the Association for Information Systems)
  
• INFORMS (Institute for Operations Research and the Management Sciences)
  
• American Association of Artificial Intelligence (AAAI)
  
• IEEE Society