Biography summary
I am a Senior Lecturer in Data Science in the School of IT at Deakin University. I serve as the inaugural director for Deakin's Bachelor of Artificial Intelligence course, the first undergraduate AI programme in Australia.
The research of my group is focused on reliable machine learning. Recognising that the data are only noisy, partial, and biased representations of reality, we aim to create machine learning models faithful to the domain and responsible in the prediction. To this end, we tackle the research challenges in uncertainty estimation and model fusion. On the application side, we work primarily on machine learning problems from our collaborators in healthcare and cyber security.
Research interests
- Robust Machine Learning
- Deep Dynamical Models
Teaching interests
- Machine Learning/Deep Learning
- Artificial Intelligence
- Data Science
Units taught
- SIT744/SIT319: Deep Learning
- SIT741: Statistical Data Analysis
- SIT215: Computational Intelligence
- SIT306: IT Internship
- SIT709: Internship
- SIT374/764: Project Management
- SIT384: Data Analytics for Cyber Security
- SIT112: Data Science Concepts
Knowledge areas
Machine Learning
Expertise
- Artificial intelligence
Research groups
Awards
- Vice-Chancellor's Award, Deakin University, 2022
- Research award for excellence in research collaboration and teamwork, School of Information Technology, 2017
- Geelong Chamber of Commerce Smart Technology Award, 2013
Publications
Robust visual question answering via semantic cross modal augmentation
A Mashrur, W Luo, N Zaidi, A Robles-Kelly
(2024), Vol. 238, Computer Vision and Image Understanding, C1
Robust federated learning under statistical heterogeneity via hessian-weighted aggregation
A Ahmad, W Luo, A Robles-Kelly
(2023), Vol. 112, pp. 633-654, Machine Learning, Berlin, Germany, C1
Distributed Optimization of Graph Convolutional Network Using Subgraph Variance
Taige Zhao, Xiangyu Song, Man Li, Jianxin Li, Wei Luo, Imran Razzak
(2023), pp. 1-12, IEEE Transactions on Neural Networks and Learning Systems, Piscataway, N.J., C1
Robust federated learning under statistical heterogeneity via Hessian spectral decomposition
A Ahmad, W Luo, A Robles-Kelly
(2023), Vol. 141, Pattern Recognition, C1
Novel-domain Object Segmentation via Reliability-aware Teacher Ensemble
J Miao, W Luo, N Zaidi, J Wang
(2023), pp. 761-768, HPCC/DSS/SmartCity/DependSys 2022 : Proceedings of the 2022 IEEE 24th Int Conf on High Performance Computing & Communications; 8th Int Conf on Data Science & Systems; 20th Int Conf on Smart City; 8th Int Conf on Dependability in Sensor, Cloud & Big Data Systems & Application Combined Conference, Hainan, China, E1
Federated Learning Under Statistical Heterogeneity on Riemannian Manifolds
Adnan Ahmad, Wei Luo, Antonio Robles-Kelly
(2023), Vol. 13935, pp. 380-392, PAKDD 2023 : Proceedings of the 27th Pacific-Asia Conference on Knowledge Discovery and Data Mining, Osaka, Japan, E1
Bio-Inspired Dual-Network Model to Tackle Statistical Heterogeneity in Federated Learning
A Ahmad, V Chau, A Robles-Kelly, S Gao, L Gao, L Chi, W Luo
(2023), Vol. 2023-June, pp. 1-8, IJCNN 2023 : Proceedings of the International Joint Conference on Neural Networks, Gold Coast, Queensland, E1
Embracing the dropouts in single-cell RNA-seq dynamics modelling
M Xiang, W Luo, J Hou, W Tao
(2023), Vol. 2023-June, pp. 1-8, IJCNN 2023 : Proceedings of the International Joint Conference on Neural Networks, Gold Coast, Queensland, E1
Do We Need an Encoder-Decoder to Model Dynamical Systems on Networks?
B Liu, W Luo, G Li, J Huang, B Yang
(2023), Vol. 2023-August, pp. 2178-2186, IJCAI 2023 : Proceedings of the 32nd International Joint Conference on Artificial Intelligence, Macao, China, E1
Backdoor Attack on Deep Neural Networks in Perception Domain
X Mo, L Zhang, N Sun, W Luo, S Gao
(2023), Vol. 2023-June, pp. 1-8, IJCNN 2023 : Proceedings of the International Joint Conference on Neural Networks, Gold Coast, Queensland, E1
A Hessian-Based Federated Learning Approach to Tackle Statistical Heterogeneity
A Ahmad, W Luo, A Robles-Kelly
(2023), Vol. 14177, pp. 408-422, ADMA 2023 : Proceedings of the 19th International Conference on Advanced Data Mining and Applications, Shenyang, China, E1
Bridging the Interpretability Gap in Coupled Neural Dynamical Models
M Xiang, W Luo, J Hou, W Tao
(2023), Vol. 14176 LNAI, pp. 524-534, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), E1
Tackling Model Mismatch with Mixup Regulated Test-Time Training
B Zhang, R Shao, J Du, P Yuen, W Luo
(2023), 2023 IEEE 10th International Conference on Data Science and Advanced Analytics, DSAA 2023 - Proceedings, E1
Robust quantification of prediction uncertainty by inducing heterogeneity in deep ensembles
A Mashrur, W Luo, N Zaidi, A Robles-Kelly
(2023), pp. 478-485, DICTA 2023 : Proceedings of the 2023 International Conference on Digital Image Computing: Techniques and Applications, Port Macquarie, N.S.W., E1
Learning Stable Task-Level Manifold for Few-Shot Learning
S Yu, W Luo, G Li, B Yang
(2023), pp. 411-417, DICTA 2023 : Proceedings of the 2023 International Conference on Digital Image Computing: Techniques and Applications, Port Macquarie, N.S.W., E1
A multiple feature fusion framework for video emotion recognition in the wild
N Samadiani, G Huang, W Luo, C Chi, Y Shu, R Wang, T Kocaturk
(2022), Vol. 34, Concurrency and Computation: Practice and Experience, C1
Cyber Code Intelligence for Android Malware Detection
Junyang Qiu, Q Han, W Luo, L Pan, S Nepal, J Zhang, Y Xiang
(2022), pp. 1-11, IEEE Transactions on Cybernetics, Piscataway, N.J., C1
Attention-based Feature Fusion for Reconstructing Gene-Regulatory Interactions
M Xiang, W Luo, J Hou, W Tao
(2022), pp. 1-7, DSAA 2022 : Proceedings of the 2022 IEEE 9th International Conference on Data Science and Advanced Analytics, Online, E1
Semantic multi-modal reprojection for robust visual question answering
Akib Mashrur, Wei Luo, Nayyar Zaidi, Antonio Robles-Kelly
(2022), DICTA 2022: Proceedings of the International Conference on Digital Image Computing: Techniques and Applications 2022, Sydney, N.S.W., E1
Machine Learning-Based Online Source Identification for Image Forensics
Yonggang Huang, Lei Pan, wei Luo, Yahui Han, Jun Zhang
(2021), pp. 27-56, Cyber Security Meets Machine Learning, Singapore, B1
Lihua Xu, Joseph Ferguson, Wanty Widjaja, Wei Luo, Lei Bao, Jianxin Li
(2021), Vol. 2, pp. 220-242, Methodological approaches to STEM education research, Cambridge, Eng., B1
Software Vulnerability Discovery via Learning Multi-Domain Knowledge Bases
Guanjun Lin, Jun Zhang, Wei Luo, Lei Pan, Olivier De Vel, Paul Montague, Yang Xiang
(2021), Vol. 18, pp. 2469-2485, IEEE TRANSACTIONS ON DEPENDABLE AND SECURE COMPUTING, C1
A Survey of Android Malware Detection with Deep Neural Models
J Qiu, J Zhang, W Luo, L Pan, S Nepal, Y Xiang
(2021), Vol. 53, ACM Computing Surveys, C1
L Gao, W Luo, U Tonmukayakul, M Moodie, G Chen
(2021), Vol. 22, pp. 341-350, European Journal of Health Economics, Germany, C1
Con2Vec: Learning embedding representations for contrast sets
D Nguyen, W Luo, B Vo, L Nguyen, W Pedrycz
(2021), Vol. 229, Knowledge-Based Systems, C1
S Rana, W Luo, T Tran, S Venkatesh, P Talman, T Phan, D Phung, B Clissold
(2021), Vol. 12, Frontiers in Neurology, Switzerland, C1
Microwave Link Failures Prediction via LSTM-based Feature Fusion Network
Zichan Ruan, Shuiqiao Yang, Lei Pan, Xingjun Ma, Wei Luo, Marthie Grobler
(2021), pp. 1-8, IJCNN 2021 : Proceedings of the International Joint Conference on Neural Networks, Shenzhen, China, E1
Impute Gene Expression Missing Values via Biological Networks: Optimal Fusion of Data and Knowledge
Mingrong Xiang, Jingyu Hou, Wei Luo, Wenjing Tao, Deshou Wang
(2021), pp. 1-8, IJCNN 2021 : Proceedings of the International Joint Conference on Neural Networks, Shenzhen, China, E1
Robust Neural Regression via Uncertainty Learning
A Mashrur, W Luo, N Zaidi, A Robles-Kelly
(2021), pp. 1-6, IJCNN 2021 : Proceedings of the 2021 International Joint Conference on Neural Networks, Shenzhen, China, E1
Ultra-short term wholesale electricity price forecasting through deep learning
A Alvarez, W Luo, S Fryer
(2021), ISGT Asia 2021 : Proceedings of the IEEE PES Innovative Smart Grid Technologies - Asia Conference, Brisbane, Qld., E1
Christopher Young, Wei Luo, Paul Gastin, Daniel Dwyer
(2020), Vol. 38, pp. 676-681, Journal of sports sciences, Abingdon, Eng., C1
MODEL: Motif-Based Deep Feature Learning for Link Prediction
L Wang, J Ren, B Xu, J Li, W Luo, F Xia
(2020), Vol. 7, pp. 503-516, IEEE Transactions on Computational Social Systems, C1
D Nguyen, W Luo, B Vo, W Pedrycz
(2020), Vol. 161, Expert Systems with Applications, C1
V Brown, J Williams, L McGivern, S Sawyer, L Orellana, W Luo, K Hesketh, D Wilfley, M Moodie
(2020), Vol. 10, BMJ Open, England, C1
Gathering intelligence on student information behavior using data mining
L Pan, N Patterson, S McKenzie, S Rajasegarar, G Wood-Bradley, J Rough, W Luo, E Lanham, J Coldwell-Neilson
(2020), Vol. 68, pp. 636-658, Library Trends, C1
Machine learning for financial risk management: A survey
A Mashrur, W Luo, N Zaidi, A Robles-Kelly
(2020), Vol. 8, pp. 203203-203223, IEEE Access, C1
A Novel Video Emotion Recognition System in the Wild Using a Random Forest Classifier
N Samadiani, G Huang, W Luo, Y Shu, R Wang, T Kocaturk
(2020), Vol. 1179, pp. 275-284, ICDS 2019 : Data science : 6th international conference, ICDS 2019, Ningbo, China, May 15-20, 2019, revised selected papers, Ningbo, China, E1
Bias-regularised neural-network metamodelling of insurance portfolio risk
Wei Luo, Akib Mashrur, Antonio Robles-Kelly, Gang Li
(2020), IJCNN : Proceedings of the 2020 International Joint Conference on Neural Networks, Online : Glasgow, United Kingdom, E1
The relationship between match performance indicators and outcome in Australian Football
C Young, W Luo, P Gastin, J Tran, D Dwyer
(2019), Vol. 22, pp. 467-471, Journal of Science and Medicine in Sport, C1
Understanding effective tactics in Australian football using network analysis
C Young, W Luo, P Gastin, J Lai, D Dwyer
(2019), Vol. 19, pp. 331-341, International Journal of Performance Analysis in Sport, C1
A review on automatic facial expression recognition systems assisted by multimodal sensor data
N Samadiani, G Huang, B Cai, W Luo, C Chi, Y Xiang, J He
(2019), Vol. 19, Sensors (Switzerland), Switzerland, C1
Predicting the Impact of Android Malicious Samples via Machine Learning
J Qiu, W Luo, L Pan, Y Tai, J Zhang, Y Xiang
(2019), Vol. 7, pp. 66304-66316, IEEE Access, C1
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
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
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
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
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
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
D Nguyen, W Luo, S Venkatesh, D Phung
(2018), Vol. 42, Journal of Medical Systems, United States, C1
D Nguyen, W Luo, D Phung, S Venkatesh
(2018), Vol. 161, pp. 313-328, Knowledge-Based Systems, 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
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, Netherlands, 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 Ashely, D Phung
(2016), Vol. 9651, pp. 152-164, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), B1
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
Consistency of the Health of the Nation Outcome Scales (HoNOS) at inpatient-to-community transition
W Luo, R Harvey, T Tran, D Phung, S Venkatesh, J Connor
(2016), Vol. 6, BMJ Open, England, C1
C Karmakar, W Luo, T Tran, M Berk, S Venkatesh
(2016), Vol. 3, JMIR Mental Health, Canada, C1
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, England, 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. 2-17, JMIR Medical Informatics, Canada, C1
W Luo, D Phung, T Tran, S Gupta, S Rana, C Karmakar, A Shilton, J Yearwood, N Dimitrova, T Ho, S Venkatesh, M Berk
(2016), Vol. 18, Journal of Medical Internet Research, Canada, 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
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
Understanding toxicities and complications of cancer treatment: A data mining approach
D Nguyen, W Luo, D Phung, S Venkatesh
(2015), Vol. 9457, pp. 431-443, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), B1
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
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
Ipoll: Automatic polling using online search
T Nguyen, D Phung, W Luo, T Tran, S Venkatesh
(2014), Vol. 8786, pp. 266-275, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), B1
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
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
Ipoll: Automatic polling using online search
T Nguyen, D Phung, W Luo, T Tran, S Venkatesh
(2014), Vol. 8786 LNCS, pp. 266-275, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 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, Berlin, Germany, 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, London, England, 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
W Luo, M Gallagher
(2011), pp. 135-148, PAKDD 2011 : Advances in Knowledge Discovery and Data Mining : Proceedings of PAKDD 2011, Shenzhen, China, 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, Amsterdam, The Netherlands, C1-1
Unsupervised DRG upcoding detection in healthcare databases
W Luo, M Gallagher
(2010), pp. 600-605, ICDMW 2010 : Proceedings of 10th IEEE International Conference on Data Mining Workshops, Sydney, New South Wales, 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
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, CIDM 2009 : Proceedings of the 2009 IEEE Symposium on Computational Intelligence and Data Mining, Nashville, Tennesee, E1-1
Mind change optimal learning of Bayes net structure
O Schulte, W Luo, R Greiner
(2007), pp. 187-202, COLT 2007 : Proceedings of the 20th Annual Conference on Learning Theory 2007, San Diego, California, E1-1
Mind change efficient learning
W Luo, O Schulte
(2006), Vol. 204, pp. 989-1011, Information and computation, Amsterdam, The Netherlands, C1-1
Learning Bayesian networks in Semi-deterministic systems
W Luo
(2006), pp. 230-241, Canadian AI 2006 : Advances in artificial intelligence : 19th Conference of the Canadian Society for Computational Studies of Intelligence, Canadian AI 2006, Quebec City, Québec, Canada, June 7-9, 2006 : proceedings, Quebec City, Quebec, E1-1
Mind change efficient learning
W Luo, O Schulte
(2005), pp. 398-412, COLT 2005 : Learning Theory : 18th annual conference on learning theory, COLT 2005 Bertinoro, Italy June 27-30, 2005 : proceedings, Bertinoro, Italy, E1-1
Compute inclusion depth of a pattern
W Luo
(2005), pp. 689-690, Learning Theory : 18th annual conference on learning theory, COLT 2005 Bertinoro, Italy June 27-30, 2005 : proceedings, Bertinoro, Italy, 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, Prof Liliana Orellana, Dr Wei Luo, Prof Kylie Hesketh, Dr Denise Wilfley
NHMRC Project Grant
- 2021: $275,140
- 2020: $230,242
- 2019: $233,282
- 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, A/Prof Niranjan Bidargaddi, A/Prof Santu Rana, Prof Truyen Tran, 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 John Fouyaxis, Dr Kit Huckvale, Prof John Grundy, Dr Leonard Hoon, Nicole Cockayne, David Varley, Dr Tanya Petrovich, Matthew Macfarlane, Dr Anju Kissoon Curumsing, Dr Tom McClean, Ms Sharon Grocott, Prof Deborah Parker, Dr Scott Barnett, Prof Jean-Guy Schneider, Dr Jessica Rivera Villicana, Prof Nilmini Wickramasinghe, A/Prof Carsten Rudolph, Mr Fernando Escorcia, Dr Gnana Bharathy
ARC Industrial Transformation Research Hubs
- 2023: $18,750
- 2021: $388,477
- 2020: $385,381
- 2019: $399,716
- 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, A/Prof Niranjan Bidargaddi, A/Prof Santu Rana, Prof Truyen Tran, 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 John Fouyaxis, Dr Kit Huckvale, Prof John Grundy, Dr Leonard Hoon, Nicole Cockayne, David Varley, Dr Tanya Petrovich, Matthew Macfarlane, Dr Anju Kissoon Curumsing, Dr Tom McClean, Ms Sharon Grocott, Prof Deborah Parker, Dr Scott Barnett, Prof Jean-Guy Schneider, Dr Jessica Rivera Villicana, Prof Nilmini Wickramasinghe, A/Prof Carsten Rudolph, Mr Fernando Escorcia, Dr Gnana Bharathy
Cancer Council Victoria Grant - Research, Uniting NSW.ACT, Interrelate Limited, Black Dog Institute, goAct, Dementia Australia (Alzheimer's Australia) Vic Inc, Unisono Pty Ltd, Aged Care & Housing Group Inc, NeoProducts Pty Ltd, Health Metrics, Uniting AgeWell
- 2022: $793,130
- 2020: $553,025
- 2019: $378,745
Unlocking factors for successful job placement through machine learning
Prof Svetha Venkatesh, Dr Wei Luo
WISE Employment Ltd
- 2018: $52,019
- 2017: $78,028
Oil / Gas Wells Surveillance based on Artificial Intelligence Methods.
Prof Gang Li, Dr Wei Luo
Shaaxi Dasheng Petroleum Engineering Technology Service Co Ltd
- 2021: $32,457
- 2019: $30,681
Supervisions
Mingrong Xiang
Thesis entitled: Machine Learning for Data with Complex Topological Relationships
Doctor of Philosophy (Information Technology), School of Information Technology
Akib Mashrur
Thesis entitled: Towards a Robust Deep Learning Framework for Uncertainty Quantification
Doctor of Philosophy (Information Technology), School of Information Technology
Kasra Majbouri Yazdi
Thesis entitled: New Approaches to Solving Social Networks Related Challenges
Doctor of Philosophy (Information Technology), School of Information Technology
Junyang Qiu
Thesis entitled: Data-Driven Android Malware Intelligence with Machine Learning through Static Analysis
Doctor of Philosophy (Information Technology), School of Information Technology
Thanh Hung Vu
Thesis entitled: Video Anomaly Detection using Deep Generative Models
Doctor of Philosophy (Information Technology), Applied Artificial Intel Ins
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
Zichan Ann Ruan
Thesis entitled: A Comprehensive Study on Microwave Links: through Microwave Link Security Needs to Modeling and Evaluation
Doctor of Philosophy (Information Technology), School of Information Technology
Najmeh Samadiani
Thesis entitled: Emotion Recognition in Unconstrained Facial Videos by Learning Reliable Features
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