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
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
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
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
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
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
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
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
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
D Nguyen, W Luo, B Vo, W Pedrycz
(2020), Vol. 161, pp. 1-17, Expert systems with applications, C1
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
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
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
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
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
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
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
D Nguyen, W Luo, D Phung, S Venkatesh
(2018), Vol. 161, pp. 313-328, Knowledge-based systems, Amsterdam, The Netherlands, C1
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
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
D Nguyen, B Vo, D Vu
(2016), Vol. 32, pp. 2313-2327, Quality and Reliability Engineering International, C1
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
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
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
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
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
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
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
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
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
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
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