LATEST NEWS


12 Oct. 2020: our paper is accepted at ICPR 2020

15 Jun. 2020: our paper is accepted in Expert Systems with Applications journal (Q1, IF: 5.452)

05 Jun. 2020: our paper gets accepted at ECML-PKDD 2020 (A conference, acceptance rate = 131/687 = 19.1%)

01 Jun. 2020: our paper gets accepted at ICML 2020 (A* conference, acceptance rate = 1088/4990 = 21.8%)

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

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, Fairness and Interpretable Machine Learning

EDUCATION


PhD in Computer Science, 05/2015 – 10/2018
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 (Google scholar, ORCID)


International journal papers

  1. Dang Nguyen, Wei Luo, Bay Vo, Witold Pedrycz (2020). Succinct Contrast Sets via False Positive Controlling with an Application in Clinical Process Redesign. Expert Systems with Applications, 161, 113670-113687 (Q1, IF: 5.452) [Paper]
  2. 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, 4, 20571-20578 (SCIE, IF: 2.584, Q1) (* equivalent first authors)
  3. 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)
  4. 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) [Source code]
  5. 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)
  6. 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)
  7. 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)
  8. 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)
  9. 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. Thomas Patrick Quinn*, Dang Nguyen*, Santu Rana, Sunil Gupta, Svetha Venkatesh (2020). DeepCoDA: personalized interpretability for compositional health data. ICML 2020 (A* conference, acceptance rate = 1088/4990 = 21.8%) (* equivalent first authors) [Source code]
  2. Phuc Luong, Dang Nguyen, Sunil Gupta, Santu Rana, Svetha Venkatesh (2020). Bayesian Optimization with Missing Inputs. ECML-PKDD 2020, Ghent, Belgum
  3. 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 (A* conference, acceptance rate = 1591/8800 = 20.6%) [Source code]
  4. 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
  5. 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 [Source code]
  6. Dang Nguyen, Cheng Li, Santu Rana, Andrew Gill, Sunil Gupta, Svetha Venkatesh (2019). Factor screening high-dimensional, stochastic combat simulations. MODSIM 2019, Canberra, Australia
  7. 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) [Source code]
  8. 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
  9. 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 [Source code]
  10. 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
  11. 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 [Source code]
  12. 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
  13. Bay Vo, Dang Nguyen, Thanh-Long Nguyen (2015). A parallel algorithm for frequent subgraph mining. ICCSAMA 2015, Metz, France. Springer AISC, 358, 163-173 [Source code]
  14. 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
  15. 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 (A2I2), 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


  • Shortlisted for the Alfred Deakin Medal for Doctoral Thesis, Deakin University, Australia, 02/2019
  • 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

  • AAAI (2021), ECML-PKDD (2020), AusDM (2019, 2020), IEEE SSCI (2020), SoICT (2019)

Invited Reviewers for Journals

  • TKDE (IEEE) (2019, 2020), Applied Intelligence (Springer) (2020), Transactions on Fuzzy Systems (IEEE) (2020), KBS (Elsevier) (2018, 2019, 2020), Transactions on Data Science (ACM) (2019), Information Systems (Elsevier) (2019), Information Sciences (Elsevier) (2019), Data Technologies and Applications (Emerald) (2019), Cluster Computing (Springer) (2019), Pattern Recognition (Elsevier) (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: 12 Oct. 2020