Picture

Xuan-Hong Dang, postdoc.,

Department of Computer Science
Aarhus University, Denmark

Contact

Email: dang@cs.au.dk
Phone: +45 8715 6224
Fax: +45 8715 4113
Postal address: Department of Computer Science,
Aarhus University, 8200 Aarhus N, Denmark.
Åbogade 34, building 5335, room 3-44

(I have moved to the UCSB from 1st Nov 2013 and the homepage will soon be updated...!)


About me


    I am a postdoc at the Data-Intensive Systems Group and have commenced this position from October 2011. Prior moving to the Aarhus Univeristy, I had been with the Monash University and the University of Melbourne (Australia) from 2008 to 2011, as a postdoctal research fellow. I obtained my PhD degree from the Nanyang Technological University in September 2008.

    Research Interests: My research interests lie in the area of unsupervised and semi-supervised learning with the objective of devising effective algorithms to discover and interpret patterns hidden in large and high-dimensional databases. Currently, my studies are focusing on identifying and understanding anomalous patterns using graph theory and spectral analyzing techniques. Exploring multiple alternative clusterings using probabilistic and non-parametric models is my another concern at the moment. Additionally, I am also interested in mining and query-processing over evolving streaming data. My studies in these areas have been published in several major journals/conferences including: Machine Learning, DMKD, KAIS, TKDD, SIGKDD, ICDE, ICDM, SDM, ECML/PKDD, DEXA, etc...

Publications

    1. X. H. Dang, I. Assent, R.T. Ng, A. Zimek, E. Schubert, Discriminative Features for Identifying and Interpreting Outliers, accepted in the 30th IEEE International Conference on Data Engineering (ICDE 2014), Chicago, IL, USA, 2014. (manuscript)

    2. B. Micenkova, R.T. Ng, X. H. Dang, I. Assent, Explaining Outliers for Validation and Analysis, accepted as regular paper in the IEEE International Conference on Data Mining (ICDM 2013), Dallas, Texas, USA, 2013. (manuscript)

    3. X. H. Dang, J. Bailey, Generating Multiple Alternative Clusterings Via Globally Optimal Subspaces, Data Mining and Knowledge Discovery Journal (DMKD 2013), (DOI) 10.1007/s10618-013-0314-1. (manuscript)

    4. X. H. Dang, J. Bailey, A Framework to Uncover Multiple Alternative Clusterings, Machine Learning Journal (ML 2013) , (DOI) 10.1007/s10994-013- 5338-7. (manuscript)

    5. X. H. Dang, B. Micenkova, I. Assent, R.T. Ng, Local Outlier Detection with Interpretation, European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD 2013), Prague, Czech Republic, Sep 2013. (manuscript)

    6. X. H. Dang, B. Micenkova, I. Assent, R.T. Ng, Outlier Detection with Space Transformation and Spectral Analysis (full paper with oral presentation), 13th SIAM International Conference on Data Mining (SDM 2013), Austin, Texas, USA, 2013. (manuscript)

    7. X. H. Dang, Kok-Leong Ong, Vincent C. S. Lee: An Adaptive Algorithm for Finding Frequent Sets in Landmark Windows, 6th International Conference on Scalable Uncertainty Management (SUM 2012), Marburg, Germany, September 17-19, 2012.

    8. X. H. Dang, Ira Assent and James Bailey: Multiple Clustering Views via Constrained Projection (workshop paper), Proc. 3rd International Workshop on Discovering, Summarizing and Using Multiple Clusterings (Multi-Clust 2012) in conjunction with the SIAM International Conference on Data Mining (SDM 2012), Anaheim, California, USA

    9. X. H. Dang, J. Bailey, A Hierarchical Information Theoretic Technique for the Discovery of Non Linear Alternative Clusterings (full paper), 16th ACM SIGKDD International Conference On Knowledge Discovery and Data Mining (SIGKDD 2010), Washington DC, USA, 2010.(manuscript)

    10. X. H. Dang, J. Bailey, Generation of Alternative Clusterings Using the CAMI Approach, 10th SIAM International Conference on Data Mining (SDM 2010), Ohio, USA, 2010.(manuscript)

    11. X. H. Dang, V. Lee, W. K. Ng, K. L. Ong, Incremental and Adaptive Clustering Stream Data over Sliding Window, 20th International Conference on Database and Expert Systems Applications (DEXA 2009), Linz, Austria, 2009. (manuscript)

    12. X. H. Dang, V. Lee, W. K. Ng, A. Ciptadi, K. L. Ong, An EM-Based Algorithm for Clustering Data Streams in Sliding Windows, 14th International Conference on Database Systems for Advanced Applications (DASFAA 2009), Brisbane, Australia, 2009.

    13. X. H. Dang, K.-L. Ong Knowledge discovery in Data Streams, Encyclopedia of Library and Information Science (3rd Ed.), 2009.

    14. Wan Li, W. K. Ng, X. H. Dang, Philip S. Yu, Density-Based Clustering of Data Streams at Multiple Resolutions, ACM Transactions on Knowledge Discovery from Data, ACM Transactions on Knowledge Discovery from Data, (TKDD) 3(3): (2009).

    15. X. H. Dang, W. K. Ng, K.-L. Ong. Online mining of frequent sets in data streams with error guarantee, International Journal of Knowledge and Information Systems (KAIS), Vol.16, No.2,pg 245-258, Springer 2008, ISSN 0219-1377.

    16. X. H. Dang, W. K. Ng, K.-L. Ong, V.C.S Lee Frequent Sets Mining in Data Stream Environments, Encyclopedia of Data Warehousing and Mining (2nd Ed.), IGI Publishing, 2008.

    17. H. K. Le, X. H. Dang, L. D. Nguyen, On the triangular norms approach for the heuristic model in expert systems . Proceedings of the 5th International Conference on Information Technology in Education and Training (Eds: Nordholm S.E., Hoang K.), 2008.

    18. X. H. Dang, W. K. Ng, K. L. Ong, V.C.S Lee, Discovering Frequent Sets from Data Streams with CPU Constraint . 6th Australasian Data Mining Conference (AusDM 2007), Gold Coast, Australia, 2007 [Best Paper Award](manuscript).

    19. X. H. Dang, W. K. Ng, K. L. Ong, Adaptive Load Shedding for Mining Frequent Patterns from Data Streams, 8th International Conference on Data Warehousing and Knowledge Discovery (DaWaK 2006), Krakow, Republic of Poland, 2006.

    20. X. H. Dang, W. K. Ng, K. L. Ong, EStream: Online Mining of Frequent Sets with Precise Error Guarantee, 8th International Conference on Data Warehousing and Knowledge Discovery (DaWak 2006), Krakow, Republic of Poland, 2006.

    21. H. K. Le, X. H. Dang, L. D. Nguyen, Some problems about Archimedean triangular norms. Journal of Informatics and Cybernetics, Vol 20, No 4, page 373-381, 2004.

    22. H. K. Le, X. H. Dang, A heuristic model based on the triangular norms. Journal of Informatics and Cybernetics, Vol 19, No 3, page 243-255, 2003.

    23. X. H. Dang, An algorithm for normalizing a data relation to the third normal form. Journal of Informatics and Cybernetics, Vol 17, No 3, page 77-86, 2001.

Awards

  • Endevour Scholarship from Australian Goverment to follow a post-doctoral position at the Monash University, 2008.
  • Best paper award at the 6th Australasian Data Mining Conference, Gold Coast, Australia, 2007.
  • Scholarship from Swedish Goverment to study ICT at Life Academy, Karlstad, Sweden, 2003.

Teaching

  • Graduate Course: Multidimensional Databases, CS, Spring 2013 (with A/Prof. Ira Assent), course page
  • Undergraduate Course: Information Systems, CS, Fall 2012 (with A/Prof. Ira Assent), course page
  • Graduate Course: Multidimensional Databases, CS, Spring 2012 (with A/Prof. Ira Assent), course page

Reviewer and external reviewer

  • The 26th Australasian Joint Conference on Artificial Intelligence, Dunedin, New Zealand, 2013
  • The 11th Australasian Data Mining Conference, Canberra, Australia, 2013
  • IEEE International Conference on Data Mining, Dallas, Texas, USA, 2013
  • The 19th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Chicago, USA, 2013
  • The European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML/PKDD), Prague, Czech Republic, 2013
  • The 4th MultiClust Workshop on Multiple Clusterings, Multi-view Data, and Multi-source Knowledge-driven Clustering in conjunction with ACM SIGKDD, Chicago, Illinois, USA, 2013
  • The European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML/PKDD), Bristol, UK, 2012
  • IEEE International Conference on Data Mining, Brussels, Belgium, 2012
  • The 21st ACM International Conference on Information and Knowledge Management (CIKM 2012), Maui, USA, 2012
  • The 10th Australasian Data Mining Conference, Sydney, 2012
  • The 10th SIAM International Conference on Data Mining, Ohio, USA, 2010
  • The 16th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, Washington DC, USA, 2010
  • Machine Learning Journal, 2010
  • IEEE International Conference on Data Mining series (ICDM 2009), Miami, FL,USA, 2009
  • The 18th ACM Conference on Information and Knowledge Management), Hong Kong, 2009
  • The Australasian Data Mining Conference, Melbourne, Australia, 2009
  • The Twenty Second International Conference on Industrial, Engineering & Other Applications of Applied Intelligent Systems, Tainan, Taiwan, 2009
  • IEEE Symposium on Computational Intelligence and Data Mining, Nashville, TN, USA, 2009.
  • The 5th International Conference on Advanced Data Mining and Applications, Beijing, China, 2009
  • Data Mining and Knowledge Discovery Journal, 2008
  • Journal of Research and Practice in Information Technology, 2008
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