Publications
The relationship between match performance indicators and outcome in Australian football
Christopher Young, Wei Luo, Paul Gastin, Jacqueline Tran, Dan Dwyer
(2019), Vol. 22, pp. 467-471, Journal of science and medicine in sport, Amsterdam, The Netherlands, 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
Understanding effective tactics in Australian football using network analysis
Christopher Young, Wei Luo, Paul Gastin, Jerry Lai, Daniel Dwyer
(2019), Vol. 19, pp. 331-341, International journal of performance analysis in sport, Abingdon, Eng., C1
A review on automatic facial expression recognition systems assisted by multimodal sensor data
Najmeh Samadiani, Guangyan Huang, Borui Cai, Wei Luo, Chi-Hung Chi, Yong Xiang, Jing He
(2019), Vol. 19, Sensors, Basel, Switzerland, C1
Predicting the impact of android malicious samples via machine learning
Junyang Qiu, Wei Luo, Lei Pan, Yonghang Tai, Jun Zhang, Yang Xiang
(2019), pp. 1-14, IEEE Access, Piscataway, N.J., C1
Deep neighbor embedding for evaluation of large portfolios of variable annuities
Xiaojuan Cheng, Wei Luo, Guojun Gan, Gang Li
(2019), Vol. 11775, pp. 472-480, KSEM 2019 : Knowledge Science, Engineering and Management, Athens, Greece, E1
Fast valuation of large portfolios of variable annuities via transfer learning
X Cheng, Wei Luo, G Gan, Gang Li
(2019), Vol. 11672, pp. 716-728, PRICAI 2019: Trends in Artificial Intelligence, Cuvu, Fiji, E1
Modelling match outcome in Australian football: improved accuracy with large databases
C Young, W Luo, P Gastin, J Tran, D Dwyer
(2019), Vol. 18, pp. 80-92, International journal of computer science in sport, Warsaw, Poland, C1
Data-Driven Android Malware Intelligence: A Survey
J Qiu, S Nepal, W Luo, L Pan, Y Tai, J Zhang, Y Xiang
(2019), Vol. 11806, pp. 183-202, Machine Learning for Cyber Security, Xi?an, China, E1
Robust anomaly detection in videos using multilevel representations
Hung Vu, Dinh Tu, Le Trung, Wei Luo, Phung Dinh
(2019), Vol. 33, pp. 5216-5223, Proceedings of the Combined Conferences : 33rd AAAI Conference on Artificial Intelligence / 31st Innovative Applications of Artificial Intelligence Conference / 9th AAAI Symposium on Educational Advances in Artificial Intelligence, Honolulu, Hawaii, E1
A3CM: automatic capability annotation for android malware
Junyang Qiu, Jun Zhang, Wei Luo, Lei Pan, Surya Nepal, Yu Wang, Yang Xiang
(2019), Vol. 7, pp. 147156-147168, IEEE Access, Piscataway, N.J., C1
Cross-project transfer representation learning for vulnerable function discovery
G Lin, J Zhang, W Luo, L Pan, Y Xiang, O De Vel, P Montague
(2018), Vol. 14, pp. 3289-3297, IEEE transactions on industrial informatics, Piscataway, N.J., C1
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
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, W Luo, D Phung, S Venkatesh
(2018), Vol. 161, pp. 313-328, Knowledge-based systems, Amsterdam, The Netherlands, C1
Keep calm and know where to focus: measuring and predicting the impact of Android Malware
J Qiu, W Luo, S Nepal, J Zhang, Y Xiang, L Pan
(2018), Vol. 11323, pp. 238-254, ADMA 2018: Proceedings of the 14th International Conference on Advanced Data Mining and Applications, Nanjing, China, E1
Batch normalized Deep Boltzmann Machines
Hung Vu, Tu Nguyen, Trung Le, Wei Luo, Dinh Phung
(2018), Vol. 95, pp. 359-374, ACML 2018 : Proceedings of the 10th Asian Conference on Machine Learning, Beijing, China, E1
M Rogers, L Matheson, B Garrard, B Maher, S Cowdery, W Luo, M Reed, S Riches, G Pitson, D Ashley
(2017), Vol. 149, pp. 74-80, Public Health, London, Eng., C1
Toxicity prediction in cancer using multiple instance learning in a multi-task framework
C Li, S Gupta, S Rana, W Luo, S Venkatesh, D Ashley, Q Phung
(2016), Vol. 9651, pp. 152-164, Advances in knowledge discovery and data mining: 20th Pacific-Asia Conference, PAKDD 2016 Auckland, New Zealand, April 19-22, 2016 proceedings, part I, Berlin, Germany, B1
Consistency of the Health of the Nation Outcome Scales (HoNOS) at inpatient-to-community transition.
W Luo, R Harvey, T Tran, Q Phung, S Venkatesh, J Connor
(2016), Vol. 6, pp. 1-6, BMJ open, London, Eng., C1
C Karmakar, W Luo, T Tran, M Berk, S Venkatesh
(2016), Vol. 3, pp. 1-10, JMIR mental health, Toronto, Ont., C1
Traffic identification in big internet data
B Wang, J Zhang, Z Zhang, W Luo, D Xia
(2016), pp. 129-156, Big data concepts, theories, and applications, Berlin, Germany, B1
Screening for post 32-week preterm birth risk: how helpful is routine perinatal data collection?
W Luo, E Huning, T Tran, D Phung, S Venkatesh
(2016), Vol. 2, pp. 1-15, Heliyon, Amsterdam, The Netherlands, C1
Forecasting daily patient outflow from a ward having no real-time clinical data
S Gopakumar, T Tran, W Luo, D Phung, S Venkatesh
(2016), Vol. 4, pp. 1-16, JMIR medical informatics, Toronto, Ont., C1
Preterm birth prediction : deriving stable and interpretable rules from high dimensional data
T Tran, W Luo, Q Phung, J Morris, K Rickard, S Venkatesh
(2016), pp. 1-13, MLHC 2016 : Proceedings on Conference on Machine Learning in Healthcare, Los Angeles, California, E1
W Luo, Q Phung, T Tran, S Gupta, S Rana, C Karmakar, A Shilton, J Yearwood, N Dimitrova, T Ho, S Venkatesh, M Berk
(2016), Vol. 18, pp. 1-10, Journal of medical internet research, Toronto, Ont., 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
Forecasting patient outflow from wards having no real-time clinical data
S Gopakumar, T Tran, W Luo, D Phung, S Venkatesh
(2016), pp. 177-183, ICHI 2016: Proceedings of the IEEE International Conference on Healthcare Informatics, Chicago, Illinois, E1
Stabilized sparse ordinal regression for medical risk stratification
T Tran, D Phung, W Luo, S Venkatesh
(2015), Vol. 43, pp. 555-582, Knowledge and information systems: an international journal, Berlin, Germany, C1
Web search activity data accurately predict population chronic disease risk in the USA
T Nguyen, T Tran, W Luo, S Gupta, S Rana, Q Phung, M Nichols, L Millar, S Venkatesh, S Allender
(2015), Vol. 69, pp. 693-699, Journal of epidemiology and community health, London, Eng., C1
W Luo, T Nguyen, M Nichols, T Tran, S Rana, S Gupta, Q Phung, S Venkatesh, S Allender
(2015), Vol. 10, pp. 1-13, PLoS One, San Francisco, Calif., C1
Understanding toxicities and complications of cancer treatment: a data mining approach
D Nguyen, W Luo, S Venkatesh, 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
Robust traffic classification with mislabelled training samples
B Wang, J Zhang, Z Zhang, W Luo, D Xia
(2015), pp. 328-335, ICPADS 2015: Proceedings of the IEEE Parallel and Distributed Systems 2015 International Conference, Melbourne, Vic., E1
T Tran, W Luo, D Phung, R Harvey, M Berk, R Kennedy, S Venkatesh
(2014), Vol. 14, pp. 1-9, BMC psychiatry, London, Eng., C1
S Gupta, T Tran, W Luo, D Phung, R Kennedy, A Broad, D Campbell, D Kipp, M Singh, M Khasraw, L Matheson, D Ashley, S Venkatesh
(2014), Vol. 4, pp. 1-7, BMJ open, London, England, C1
S Rana, T Tran, W Luo, D Phung, R Kennedy, S Venkatesh
(2014), Vol. 38, pp. 377-382, Australian health review, Melbourne, Vic., C1
Detecting contaminated birthdates using generalized additive models
W Luo, M Gallagher, B Loveday, S Ballantyne, J Connor, J Wiles
(2014), Vol. 15, pp. 1-9, BMC bioinformatics, London, England, C1
iPoll: Automatic polling using online search
T Nguyen, D Phung, W Luo, T Tran, S Venkatesh
(2014), Vol. 8786, pp. 266-275, Web Information Systems Engineering ? WISE 2014, Berlin, Germany, B1
A framework for feature extraction from hospital medical data with applications in risk prediction
T Truyen, W Luo, P Dinh, S Gupta, S Rana, R Kennedy, A Larkins, S Venkatesh
(2014), Vol. 15, pp. 1-9, BMC Bioinformatics, London, Eng., C1
Individualized arrhythmia detection with ECG signals from wearable devices
B Nguyen, W Lou, T Caelli, S Venkatesh, D Phung
(2014), pp. 570-576, DSAA 2014 - Proceedings of the 2014 IEEE International Conference on Data Science and Advanced Analytics, Shanghai, China, E1
Unsupervised inference of significant locations from WiFi data for understanding human dynamics
T Nguyen, T Nguyen, W Luo, Venkatesh, Q Phung
(2014), pp. 232-235, MUM 2014 : Proceedings of the 13th International Conference on Mobile and Ubiquitous Multimedia, Melbourne, Victoria, E1-1
Speed up health research through topic modeling of coded clinical data
W Luo, Q Phung, T Nguyen, T Tran, S Venkatesh
(2014), pp. 1-4, IAPR 2014 : Proceedings of 2nd International Workshop on Pattern Recognition for Healthcare Analytics, Stockholm, Sweden, E1-1
Parameter-free search of time-series discord
W Luo, M Gallagher, J Wiles
(2013), Vol. 28, pp. 300-310, Journal of Computer Science and Technology, C1
Estimating the intensity of ward admission and its effect on emergency department access block
W Luo, J Cao, M Gallagher, J Wiles
(2013), Vol. 32, pp. 2681-2694, Statistics in Medicine, C1
An integrated framework for suicide risk prediction
T Tran, Q Phung, W Luo, R Harvey, M Berk, S Venkatesh
(2013), pp. 1410-1418, KDD'13: Proceedings of the 19th ACM SIGKDD international conference on Knowledge discovery and data mining, Chicago, Ill., E1-1
Faster and Parameter-Free Discord Search in Quasi-Periodic Time Series
Wei Luo, Marcus Gallagher
(2011), Vol. 6635, pp. 135-148, ADVANCES IN KNOWLEDGE DISCOVERY AND DATA MINING, PT II, Shenzhen, PEOPLES R CHINA, E1-1
Faster and parameter-free discord search in quasi-periodic time series
W Luo, M Gallagher
(2011), Vol. 6635 LNAI, pp. 135-148, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), E1-1
Unsupervised DRG upcoding detection in healthcare databases
W Luo, M Gallagher
(2010), pp. 600-605, Proceedings - IEEE International Conference on Data Mining, ICDM, E1-1
W Luo, M Gallagher, D O'Kane, J Connor, M Dooris, C Roberts, L Mortimer, J Wiles
(2010), pp. 45-52, HIKM 2010 : Proceedings of the 4th Australasian Workshop on Health Informatics and Knowledge Management, Brisbane, Queensland, E1-1
Mind change optimal learning of Bayes net structure from dependency and independency data
O Schulte, W Luo, R Greiner
(2010), Vol. 208, pp. 63-82, Information and Computation, C1-1
A new hybrid method for bayesian network learning with dependency constraints
O Schulte, G Frigo, R Greiner, W Luo, H Khosravi
(2009), pp. 53-60, 2009 IEEE Symposium on Computational Intelligence and Data Mining, CIDM 2009 - Proceedings, E1-1
Mind change optimal learning of bayes net structure
O Schulte, W Luo, R Greiner
(2007), Vol. 4539 LNAI, pp. 187-202, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), E1-1
Learning bayesian networks in semi-deterministic systems
W Luo
(2006), Vol. 4013 LNAI, pp. 230-241, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), E1-1
Mind change efficient learning
W Luo, O Schulte
(2006), Vol. 204, pp. 989-1011, Information and Computation, C1-1
Mind change efficient learning
W Luo, O Schulte
(2005), Vol. 3559 LNAI, pp. 398-412, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), E1-1
Compute inclusion depth of a pattern
W Luo
(2005), Vol. 3559 LNAI, pp. 689-690, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), E1-1
Funded Projects at Deakin
Australian Competitive Grants
Preventing obesity and promoting healthy body image in Australian secondary schools: a web-based system tailored to individual needs
Prof Jo Williams, Prof Craig Taylor, Prof Susan Sawyer, Prof Marj Moodie, A/Prof Liliana Orellana, Dr Wei Luo, A/Prof Kylie Hesketh, Dr Denise Wilfley
NHMRC Project Grant
- 2019: $213,842
- 2018: $334,806
- 2017: $228,521
ARC Research Hub for Digital Enhanced Living
Prof Kon Mouzakis, Prof Svetha Venkatesh, Prof Anthony Maeder, Prof Alison Hutchinson, Prof Michael Berk, Prof Ralph Maddison, Prof Abbas Kouzani, Prof Rajesh Vasa, Prof Helen Christensen, Prof Patricia Williams, Prof John Yearwood, Prof Susan Gordon, Prof David Powers, Prof Nilmini Wickramasinghe, A/Prof Niranjan Bidargaddi, A/Prof Santu Rana, A/Prof Truyen Tran, A/Prof Sunil Gupta, Dr Wei Luo, A/Prof Mohamed Abdelrazek, Dr Felix Tan, Prof Henning Langberg, A/Prof Lars Kayser, Prof Finn Kensing, Prof Freimut Bodendorf, Prof James Warren, Dr Roopak Sinha, Prof A Smeaton, Mr Fonda Voukelatos, Mr Jeffrey Fiebig, Mr John Fouyaxis, Dr Kit Huckvale, Prof John Grundy, David Varley, Dr Leonard Hoon, Nicole Cockayne, Dr Tanya Petrovich, Dr Hermant Ghayvat, Mr Voytek Szapirko, Matthew Macfarlane, Dr Anju Kissoon Curumsing, Dr Scott Barnett, Dr Tom McClean, Prof Deborah Parker
ARC Industrial Transformation Research Hubs
- 2019: $411,658
- 2018: $449,083
- 2017: $601,698
Industry and Other Funding
ARC Research Hub for Digital Enhanced Living
Prof Kon Mouzakis, Prof Svetha Venkatesh, Prof Anthony Maeder, Prof Alison Hutchinson, Prof Michael Berk, Prof Ralph Maddison, Prof Abbas Kouzani, Prof Rajesh Vasa, Prof Helen Christensen, Prof Patricia Williams, Prof John Yearwood, Prof Susan Gordon, Prof David Powers, Prof Nilmini Wickramasinghe, A/Prof Niranjan Bidargaddi, A/Prof Santu Rana, A/Prof Truyen Tran, A/Prof Sunil Gupta, Dr Wei Luo, A/Prof Mohamed Abdelrazek, Dr Felix Tan, Prof Henning Langberg, A/Prof Lars Kayser, Prof Finn Kensing, Prof Freimut Bodendorf, Prof James Warren, Dr Roopak Sinha, Prof A Smeaton, Mr Fonda Voukelatos, Mr Jeffrey Fiebig, Mr John Fouyaxis, Dr Kit Huckvale, Prof John Grundy, David Varley, Dr Leonard Hoon, Nicole Cockayne, Dr Tanya Petrovich, Dr Hermant Ghayvat, Mr Voytek Szapirko, Matthew Macfarlane, Dr Anju Kissoon Curumsing, Dr Scott Barnett, Dr Tom McClean, Prof Deborah Parker
- 2019: $328,745
Unlocking factors for successful job placement through machine learning
Prof Svetha Venkatesh, Dr Wei Luo
- 2018: $52,019
- 2017: $78,028
Oil / Gas Wells Surveillance based on Artificial Intelligence Methods.
A/Prof Gang Li, Dr Wei Luo
- 2019: $30,681
Supervisions
Khanh Nguyen
Thesis entitled: Nonparametric Online Machine Learning with Kernels
Doctor of Philosophy (Information Technology), Applied Artificial Intel Ins
Dang Pham Hai Nguyen
Thesis entitled: Representation Learning in Complex Data via Pattern Discovery
Doctor of Philosophy (Information Technology), School of Information Technology
Christopher Young
Thesis entitled: Identifying Optimal Technical and Tactical Performance Characteristics in Australian Football
Doctor of Philosophy (Nutrition & Exercise) (High Cost), School of Exercise and Nutrition Sciences
Thanh Binh Nguyen
Thesis entitled: Making Sense of Pervasive Signals: a Machine Learning Approach
Doctor of Philosophy (Information Technology), School of Information Technology