LATEST NEWS


19 Nov. 2019: our paper is accepted at ACS Omega journal (Q1, IF: 2.584)

11 Nov. 2019: our paper is accepted at AAAI 2020 (A* conference, acceptance rate = 1591/8800 = 20.6%)

10 Sep. 2019: our two papers are accepted at AI 2019

04 Sep. 2019: our paper is accepted at MODSIM 2019

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

RESEARCH INTERESTS


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

EDUCATION


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. David Rubín de Celis Leal*, Dang Nguyen*, Pratibha Vellanki*, Cheng Li, Santu Rana, Nathan Thompson, Sunil Gupta, Keiran Pringle, Surya Subianto, Svetha Venkatesh, Teo Slezak, Murray Height, Alessandra Sutti (2019). Efficient Bayesian Function Optimization of Evolving Material Manufacturing Processes. ACS Omega (SCIE, IF: 2.584, Q1)
  2. 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)
  3. 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)
  4. 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)
  5. 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)
  6. 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)
  7. 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)
  8. 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, Sunil Gupta, Santu Rana, Alistair Shilton, Svetha Venkatesh (2020). Bayesian Optimization for Categorical and Category-Specific Continuous Inputs. AAAI 2020, New York, USA
  2. Phuc Luong, Sunil Gupta, Dang Nguyen, Santu Rana, Svetha Venkatesh (2019). Bayesian Optimization with Discrete Variables. AI 2019, Adelaide, Australia. Springer LNCS, 11919, 473-484
  3. Deepthi Kuttichira, Sunil Gupta, Dang Nguyen, Santu Rana, Svetha Venkatesh (2019). Detection of Compromised Models Using Bayesian Optimization. AI 2019, Adelaide, Australia. Springer LNCS, 11919, 485-496
  4. Dang Nguyen, Cheng Li, Santu Rana, Andrew Gill, Sunil Gupta, Svetha Venkatesh (2019). Factor screening high-dimensional, stochastic combat simulations. MODSIM 2019, Canberra, Australia
  5. 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)
  6. 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
  7. 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
  8. 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
  9. 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
  10. 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
  11. Bay Vo, Dang Nguyen, Thanh-Long Nguyen (2015). A parallel algorithm for frequent subgraph mining. ICCSAMA 2015, Metz, France. Springer AISC, 358, 163-173
  12. 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
  13. Dang Nguyen, Bay Vo (2013). Mining Class-Association Rules with Constraints. KSE 2013, Ha Noi, Vietnam. Springer AISC, 245, 307-318

TEACHING / RESEARCH EXPERIENCE


  • Associate Research Fellow, 06/2018 – present
    Applied Artificial Intelligence Institute, 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

AWARDS AND SCHOLARSHIPS


  • 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

CERTIFICATES


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

PROFESSIONAL SERVICES


Program Committee Members

  • AusDM (2019), SoICT (2019)

Invited Reviewers for Journals

  • Information Systems (Elsevier) (2019), Information Sciences (Elsevier) (2019), Data Technologies and Applications (Emerald) (2019), 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)

CONTACT DETAILS


Dang Nguyen

Name: Dang Nguyen

Email: nguyenphamhaidang [at] outlook.com


Last update: 02 Dec. 2019