08 Feb. 2019: my thesis is shortlisted for the Alfred Deakin Medal for Doctoral Thesis

12 Sep. 2018: our paper receives the Best Student Machine Learning Paper Runner Up Award at ECML-PKDD 2018

23 Jul. 2018: our paper is accepted in Knowledge-Based Systems (SCI, IF: 4.396, Q1)

15 Jun. 2018: our paper is accepted at ECML-PKDD 2018 (acceptance rate 26.0%)


Data Mining, Machine Learning, Representation Learning, Bayesian Optimization, Health Informatics


PhD in Computer Science, 05/2015 – 10/2018
Center for Pattern Recognition and Data Analytics, Deakin University, Geelong, Australia

MSc in Computer Science, 2006 – 2009
University of Information Technology (Vietnam National University), HCMC, Vietnam

BSc in Mathematics and Computer Science, 2001 – 2005
University of Science (Vietnam National University), HCMC, Vietnam

PUBLICATIONS (DBLPGoogle scholar, ORCID, Scopus ID)

International journal papers

  1. Dang Nguyen, Wei Luo, Dinh Phung, Svetha Venkatesh (2018). LTARM: A novel temporal association rule mining method to understand toxicities in a routine cancer treatment. Knowledge-Based Systems, 161, 313-328 (SCI, IF: 4.396, Q1)
  2. Dang Nguyen, Wei Luo, Svetha Venkatesh, Dinh Phung (2018). Effective Identification of Similar Patients Through Sequential Matching over ICD Code Embedding. Journal of Medical Systems, 42(5), Article 94 (SCIE, IF: 2.46, Q2)
  3. Dang Nguyen, Loan T.T. Nguyen, Bay Vo, Witold Pedrycz (2016). Efficient mining of class association rules with the itemset constraint. Knowledge-Based Systems, 103, 73-88 (SCI, IF: 2.947, Q1)
  4. Dang Nguyen, Bay Vo, Duc-Lung Vu (2016). A Parallel Strategy for the Logical-probabilistic Calculus-based Method to Calculate Two-terminal Reliability. Quality and Reliability Engineering International, 32(7), 2313–2327 (SCIE, IF: 1.457, Q1)
  5. Dang Nguyen, Loan T.T. Nguyen, Bay Vo, Tzung-Pei Hong (2015). A Novel Method for Constrained Class Association Rule Mining. Information Sciences, 320, 107-125 (SCI, IF: 4.038, Q1)
  6. Dang Nguyen, Bay Vo, Bac Le (2015). CCAR: An efficient method for mining class association rules with itemset constraints. Engineering Applications of Artificial Intelligence, 37, 115–124 (SCIE, IF: 2.207, Q1)
  7. Dang Nguyen, Bay Vo, Bac Le (2014). Efficient strategies for parallel mining class association rules. Expert Systems with Applications, 41(10), 4716-4729 (SCIE, IF: 2.240, Q1)

International conference papers

  1. Dang Nguyen, Wei Luo, Tu Dinh Nguyen, Svetha Venkatesh, Dinh Phung (2018). Sqn2Vec: Learning Sequence Representation via Sequential Patterns with a Gap Constraint. ECML-PKDD 2018, Dublin, Ireland. Springer LNCS, 11052, 569-584 (Best Student Machine Learning Paper Runner Up Award)
  2. Dang Nguyen, Tu Dinh Nguyen, Wei Luo, Svetha Venkatesh (2018). Trans2Vec: Learning Transaction Embedding via Items and Frequent Itemsets. PAKDD 2018, Melbourne, Australia. Springer LNAI, 10939, 361-372
  3. Dang Nguyen, Wei Luo, Tu Dinh Nguyen, Svetha Venkatesh, Dinh Phung (2018). Learning Graph Representation via Frequent Subgraphs. SDM 2018, San Diego, USA. SIAM, 306-314
  4. Dang Nguyen, Wei Luo, Dinh Phung, Svetha Venkatesh (2016). Control Matching via Discharge Code Sequences. NIPS 2016 Workshop on Machine Learning for Health, Barcelona, Spain
  5. Dang Nguyen, Wei Luo, Dinh Phung, Svetha Venkatesh (2016). Exceptional Contrast Set Mining: Moving Beyond the Deluge of the Obvious. AI 2016, Tasmania, Australia. Springer LNAI, 9992, 455-468
  6. Dang Nguyen, Wei Luo, Dinh Phung, Svetha Venkatesh (2015). Understanding Toxicities and Complications of Cancer Treatment: A Data Mining Approach. AI 2015, Canberra, Australia. Springer LNAI, 9457, 431-443
  7. Bay Vo, Dang Nguyen, Thanh-Long Nguyen (2015). A parallel algorithm for frequent subgraph mining. ICCSAMA 2015, Metz, France. Springer AISC, 358, 163-173
  8. Dang Nguyen, Bay Vo, Bac Le (2014). A novel method for mining class association rules with itemset constraints. ICCCI 2014, Seoul, Korea. Springer LNAI, 8733, 494-503
  9. Dang Nguyen, Bay Vo (2013). Mining Class-Association Rules with Constraints. KSE 2013, Ha Noi, Vietnam. Springer AISC, 245, 307-318


  • Associate Research Fellow, 06/2018 – present
    Faculty of Health, Deakin University, Geelong, Australia
  • Research Assistant, 06/2017 – 08/2017
    School of Exercise and Nutrition Sciences, Deakin University, Geelong, Australia
  • Researcher, 08/2014 – 08/2017
    Division of Data Science, Ton Duc Thang University, HCMC, Vietnam
  • Lecturer, 08/2005 – 07/2007
    NIIT centers, Hoa Sen University, HCMC, Vietnam


  • Best Student Machine Learning Paper Runner Up Award, The European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, Ireland, 09/2018
  • Certificate of Outstanding Reviewer, Knowledge-Based Systems, Elsevier, 05/2018
  • Student Travel Award, The SIAM International Conference on Data Mining, USA, 05/2018
  • Student Travel Award, The 29th Australasian Joint Conference on Artificial Intelligence, Australia, 12/2016
  • Postgraduate Research Scholarship, Deakin University, Australia, 05/2015
  • Extra Mile Award, U.S. Consulate General, Vietnam, 04/2015
  • Franklin Award, U.S. Consulate General, Vietnam, 10/2012


  • IELTS of 6.5 with all bands at 6.0 and above, 21 June 2014
  • Microsoft Certified System Administrator (MCSA), 30 June 2012


Program Committee Members

  • AusDM (2019)

Invited Reviewers for Journals

  • Cluster Computing (Springer) (2019), Pattern Recognition (Elsevier) (2019), TKDE (IEEE) (2019), KBS (Elsevier) (2018, 2019), BMJ Open (BMJ) (2018), Machine Learning (Springer) (2018), WWWJ (Springer) (2016, 2017), DKE (Elsevier) (2017), VJCS (Springer) (2017)

Invited Reviewers for Conferences

  • PAKDD (2018), ACIIDS (2015, 2016, 2017, 2018), IJCRS (2018), INISTA (2017), KSE (2013, 2014), CISIM (2014, 2016), ICTCC (2014), ICCASA (2013)


Dang Nguyen

Name: Dang Nguyen

Email: nguyenphamhaidang [at]

Last update: 27 Jun. 2019