Profile image of Dang Nguyen

Dr Dang Nguyen

STAFF PROFILE

Position

Alfred Deakin Postdoctoral Research Fellow

Faculty

Applied Artificial Intel Inst

Department

A2I2P

Campus

Geelong Waurn Ponds Campus

Qualifications

Doctor of Philosophy, Deakin University, 2018

Research interests

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

Awards

  • 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

Publications

Filter by

2022

Verification of integrity of deployed deep learning models using Bayesian Optimization

D Kuttichira, S Gupta, D Nguyen, S Rana, S Venkatesh

(2022), Vol. 241, pp. 1-12, Knowledge-Based Systems, Amsterdam, The Netherlands, C1

journal article
2021

Fairness improvement for black-box classifiers with Gaussian process

D Nguyen, S Gupta, S Rana, A Shilton, S Venkatesh

(2021), Vol. 576, pp. 542-556, Information Sciences, Amsterdam, The Netherlands, C1

journal article

Con2Vec: Learning embedding representations for contrast sets

D Nguyen, W Luo, B Vo, L Nguyen, W Pedrycz

(2021), Vol. 229, pp. 1-10, Knowledge-Based Systems, Amsterdam, The Netherlands, C1

journal article

Adaptive cost-aware Bayesian optimization

P Luong, D Nguyen, S Gupta, S Rana, S Venkatesh

(2021), Vol. 232, pp. 1-10, Knowledge-Based Systems, Amsterdam, The Netherlands, C1

journal article

Bayesian Optimization with Missing Inputs

P Luong, D Nguyen, S Gupta, S Rana, S Venkatesh

(2021), Vol. 12458, pp. 691-706, ECML PKDD 2020 : Joint European Conference on Machine Learning and Knowledge Discovery in Databases, Belgium, Ghent, E1

conference

Factor screening using Bayesian active learning and gaussian process meta-modelling

C Li, D Nguyen, S Rana, S Gupta, A Gill, S Venkatesh

(2021), pp. 3288-3295, ICPR 2020 : Proceedings of the 25th International Conference on Pattern Recognition, Online from Milan, Italy, E1

conference

Knowledge Distillation with Distribution Mismatch

D Nguyen, S Gupta, T Nguyen, S Rana, P Nguyen, T Tran, K Le, S Ryan, S Venkatesh

(2021), Vol. 12976, pp. 250-265, ECML PKDD 2021 : Machine Learning and Knowledge Discovery in Databases. Research Track, Bilbao, Spain, E1

conference

Fast Conditional Network Compression Using Bayesian HyperNetworks

P Nguyen, T Tran, K Le, S Gupta, S Rana, D Nguyen, T Nguyen, S Ryan, S Venkatesh

(2021), Vol. 12977, pp. 330-345, ECML PKDD 2021 : Machine Learning and Knowledge Discovery in Databases. Research Track, Bilbao, Spain, E1

conference
2020

Succinct contrast sets via false positive controlling with an application in clinical process redesign

D Nguyen, W Luo, B Vo, W Pedrycz

(2020), Vol. 161, pp. 1-17, Expert systems with applications, C1

journal article

DeepCoDA: Personalized interpretability for compositional health data

T Quinn, D Nguyen, S Rana, S Gupta, S Venkatesh

(2020), Vol. PartF168147-11, pp. 7833-7842, ICML 2020 : Proceedings of the 37th International Conference on Machine Learning, Online, E1

conference

Bayesian optimization for categorical and category-specific continuous inputs

D Nguyen, S Gupta, S Rana, A Shilton, S Venkatesh

(2020), pp. 5256-5263, AAAI-20 : Proceedings of the Thirty-fourth AAAI Conference on Artificial Intelligence, New York, N.Y., E1

conference
2019

Efficient bayesian function optimization of evolving material manufacturing processes

D Rubín De Celis Leal, D Nguyen, P Vellanki, C Li, S Rana, N Thompson, S Gupta, K Pringle, S Subianto, S Venkatesh, T Slezak, M Height, A Sutti

(2019), Vol. 4, pp. 20571-20578, ACS omega, Washington, D.C., C1

journal article

Sqn2Vec: learning sequence representation via sequential patterns with a gap constraint

D Nguyen, W Luo, T Nguyen, S Venkatesh, D Phung

(2019), Vol. 11052, pp. 569-584, ECML-PKDD 2018 : Proceedings of the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, Dublin, Ireland, E1

conference

Bayesian Optimization with Discrete Variables

P Luong, S Gupta, D Nguyen, S Rana, S Venkatesh

(2019), Vol. 11919, pp. 473-484, AI 2019 : Advances in Artificial Intelligence : Proceedings of the 32nd Australian Joint Conference, Adelaide, South Australia, E1

conference

Detection of Compromised Models Using Bayesian Optimization

D Kuttichira, S Gupta, D Nguyen, S Rana, S Venkatesh

(2019), Vol. 11919, pp. 485-496, AI 2019 : Advances in Artificial Intelligence : Proceedings of the 32nd Australian Joint Conference, Adelaide, South Australia, E1

conference
2018

Effective identification of similar patients through sequential matching over ICD code embedding

Dang Nguyen, Wei Luo, Svetha Venkatesh, Dinh Phung

(2018), Vol. 42, pp. 1-13, Journal of medical systems, New York, N.Y., C1

journal article

LTARM: a novel temporal association rule mining method to understand toxicities in a routine cancer treatment

D Nguyen, W Luo, D Phung, S Venkatesh

(2018), Vol. 161, pp. 313-328, Knowledge-based systems, Amsterdam, The Netherlands, C1

journal article

Learning graph representation via frequent subgraphs

D Nguyen, W Luo, T Nguyen, S Venkatesh, D Phung

(2018), Vol. PRDT18, pp. 306-314, SDM 2018 : Proceedings of the SIAM International Conference on Data Mining, San Diego, Calif., E1

conference

Trans2Vec: Learning transaction embedding via items and frequent itemsets

D Nguyen, T Nguyen, W Luo, S Venkatesh

(2018), Vol. 10939, pp. 361-372, PAKDD 2018 : Advances in Knowledge Discovery and Data Mining : Proceedings of 22nd Pacific-Asia Conference, Melbourne, Victoria, E1

conference
2016

A Parallel Strategy for the Logical-probabilistic Calculus-based Method to Calculate Two-terminal Reliability

D Nguyen, B Vo, D Vu

(2016), Vol. 32, pp. 2313-2327, Quality and Reliability Engineering International, C1

journal article

Efficient mining of class association rules with the itemset constraint

D Nguyen, L Nguyen, B Vo, W Pedrycz

(2016), Vol. 103, pp. 73-88, Knowledge-Based Systems, C1

journal article

Exceptional contrast set mining: moving beyond the deluge of the obvious

D Nguyen, W Luo, D Phung, S Venkatesh

(2016), Vol. LNAI 9992, pp. 455-468, AI 2016 : Advances in artificial intelligence : Proceedings of the 29th Australian Joint Conference, Hobart, Tas., E1

conference
2015

Understanding toxicities and complications of cancer treatment: a data mining approach

D Nguyen, D Nguyen, W Luo, W Luo, S Venkatesh, S Venkatesh, Q Phung, Q Phung

(2015), Vol. 9457, pp. 431-443, AI 2015: Advances in artificial intelligence. 28th Australasian Joint Conference Canberra, ACT, Australia, November 30 - December 4, 2015 Proceedings, Berlin, Germany, B1

book chapter

A parallel algorithm for frequent subgraph mining

B Vo, D Nguyen, T Nguyen

(2015), Vol. 358, pp. 163-173, Advances in Intelligent Systems and Computing, Metz, FRANCE, C1

journal article

A novel method for constrained class association rule mining

D Nguyen, L Nguyen, B Vo, T Hong

(2015), Vol. 320, pp. 107-125, Information Sciences, Amsterdam, The Netherlands, C1

journal article

CCAR: An efficient method for mining class association rules with itemset constraints

D Nguyen, B Vo, B Le

(2015), Vol. 37, pp. 115-124, Engineering Applications of Artificial Intelligence, Amsterdam, The Netherlands, C1

journal article
2014

Efficient strategies for parallel mining class association rules

D Nguyen, B Vo, B Le

(2014), Vol. 41, pp. 4716-4729, Expert Systems with Applications, C1-1

journal article

Mining class-association rules with constraints

D Nguyen, B Vo

(2014), Vol. 245, pp. 307-318, Advances in Intelligent Systems and Computing, Hanoi, VIETNAM, E1-1

conference

A novel method for mining class association rules with itemset constraints

D Nguyen, B Vo, B Le

(2014), Vol. 8733, pp. 494-503, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Seoul, SOUTH KOREA, E1-1

conference

Funded Projects at Deakin

Other Public Sector Funding

Al Algorithmic Assurance

Prof Svetha Venkatesh, A/Prof Sunil Gupta, A/Prof Santu Rana, A/Prof Truyen Tran, Dr Anh Cat Le Ngo, Dr Phuoc Nguyen, Mr Stephan Jacobs, Dr Dang Nguyen

Department of Defence

  • 2021: $248,140
  • 2020: $208,820
  • 2019: $80,640

Supervisions

Associate Supervisor
2021

Deepthi Praveenlal Kuttichira

Thesis entitled: Tackling Practical Challenges in Neural Network Model Deployment

Doctor of Philosophy (Information Technology), Applied Artificial Intel Ins

Huu Phuc Luong

Thesis entitled: Bayesian Optimization for Discrete, Missing and Cost-sensitive Inputs

Doctor of Philosophy (Information Technology), Applied Artificial Intel Ins