Dr Wei Luo

STAFF PROFILE

Position

Senior Lecturer, Data Science

Faculty

Faculty of Sci Eng & Built Env

Department

School of Info Technology

Campus

Melbourne Burwood Campus

Qualifications

Doctor of Philosophy, Simon Fraser University, 2008
Master of Engineering, , 2001
Bachelor of Engineering, , 1999

Publications

Filter by

2021

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

book chapter

A sociocultural framing of multimodal learning analytics: Potential for formative assessment in primary mathematics

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

book chapter

Mapping MacNew Heart Disease Quality of Life Questionnaire onto country-specific EQ-5D-5L utility scores: a comparison of traditional regression models with a machine learning technique

Lan Gao, Wei Luo, Utsana Tonmukayakul, Marj Moodie, Gang Chen

(2021), pp. 1-10, The European Journal of Health Economics, New York, N.Y., 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

Application of Machine Learning Techniques to Identify Data Reliability and Factors Affecting Outcome After Stroke Using Electronic Administrative Records

Santu Rana, Wei Luo, Truyen Tran, Svetha Venkatesh, Paul Talman, Thanh Phan, Dinh Phung, Benjamin Clissold

(2021), Vol. 12, pp. 1-13, Frontiers in Neurology, Lausanne, Switzerland, C1

journal article

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

conference

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

conference

Robust Neural Regression via Uncertainty Learning

A Mashrur, W Luo, N Zaidi, A Robles-Kelly

(2021), Vol. 2021-July, 2021 International Joint Conference on Neural Networks (IJCNN), Shenzhen, China, E1

conference
2020

Understanding the relative contribution of technical and tactical performance to match outcome in Australian Football

Christopher Young, Wei Luo, Paul Gastin, Daniel Dwyer

(2020), Vol. 38, pp. 676-681, Journal of sports sciences, Abingdon, Eng., C1

journal article

A multiple feature fusion framework for video emotion recognition in the wild

Najmeh Samadiani, Guangyan Huang, Wei Luo, Chi-Hung Chi, Yanfeng Shu, Rui Wang, Tuba Kocaturk

(2020), pp. 1-13, Concurrency and Computation: Practice & Experience, London, Eng., C1

journal article

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, Piscataway, N.J., C1

journal article

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

Protocol for economic evaluation alongside the SHINE (Supporting Healthy Image, Nutrition and Exercise) cluster randomised controlled trial

V Brown, J Williams, L McGivern, S Sawyer, L Orellana, W Luo, K Hesketh, D Wilfley, M Moodie

(2020), Vol. 10, pp. 1-7, BMJ open, London, Eng., C1

journal article

Gathering Intelligence on Student Information Behavior Using Data Mining

Lei 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, Baltimore, Md., C1

journal article

Machine learning for financial risk management: A survey

Akib Mashrur, Wei Luo, Nayyar Zaidi, Antonio Robles-Kelly

(2020), Vol. 8, pp. 203203-203223, IEEE Access, Piscataway, N.J., C1

journal article

A Survey of Android Malware Detection with Deep Neural Models

Junyang Qiu, Jun Zhang, Wei Luo, Lei Pan, Surya Nepal, Yang Xiang

(2020), Vol. 53, pp. 1-36, ACM Computing Surveys, New York, N.Y., C1

journal article

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

conference

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

conference
2019

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

journal article

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

journal article

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

journal article

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

journal article

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

journal article

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

journal article

Software vulnerability discovery via learning multi-domain knowledge bases

Guanjun Lin, Jun Zhang, Wei Luo, Lei Pan, Olivier De Vel, Paul Montague, Yang Xiang

(2019), pp. 1-17, IEEE transactions on dependable and secure computing, Piscataway, N.J., 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

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

conference

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

conference

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

conference

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

conference
2018

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

journal article

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

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

conference

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

conference
2017

Comparison of outcomes for cancer patients discussed and not discussed at a multidisciplinary meeting

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

journal article
2016

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

book chapter

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

book chapter

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

journal article

Predicting risk of suicide attempt using history of physical illnesses from electronic medical records

C Karmakar, W Luo, T Tran, M Berk, S Venkatesh

(2016), Vol. 3, pp. 1-10, JMIR mental health, Toronto, Ont., C1

journal article

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

journal article

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

journal article

Guidelines for developing and reporting machine learning predictive models in biomedical research : a multidisciplinary view

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

journal article

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

conference

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

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

conference
2015

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

book chapter

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

journal article

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

journal article

Is demography destiny? Application of machine learning techniques to accurately predict population health outcomes from a minimal demographic dataset

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

journal article

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

conference
2014

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

book chapter

Risk stratification using data from electronic medical records better predicts suicide risks than clinician assessments

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

journal article

Machine-learning prediction of cancer survival: a retrospective study using electronic administrative records and a cancer registry

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

journal article

Predicting unplanned readmission after myocardial infarction from routinely collected administrative hospital data

S Rana, T Tran, W Luo, D Phung, R Kennedy, S Venkatesh

(2014), Vol. 38, pp. 377-382, Australian health review, Melbourne, Vic., C1

journal article

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

journal article

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

journal article

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

conference

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

conference

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

conference
2013

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

journal article

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

journal article

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

conference
2011

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

conference
2010

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

journal article

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

conference

Visualising a state-wide patient data collection : a case study to expand the audience for healthcare data

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

conference
2009

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

conference
2007

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

conference
2006

Mind change efficient learning

W Luo, O Schulte

(2006), Vol. 204, pp. 989-1011, Information and Computation, C1-1

journal article

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

conference
2005

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

conference

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

conference

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: $225,115
  • 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, 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 John Fouyaxis, Prof John Grundy, Dr Kit Huckvale, David Varley, Nicole Cockayne, Dr Leonard Hoon, Dr Tanya Petrovich, Matthew Macfarlane, Dr Anju Kissoon Curumsing, Dr Tom McClean, Prof Deborah Parker, Ms Sharon Grocott, Dr Scott Barnett, Mr Steven Strange, Prof Jean-Guy Schneider, A/Prof Carsten Rudolph, Prof Nilmini Wickramasinghe, Dr Jordan Vincent, Mr Fernando Escorcia, Dr Gnana Bharathy

ARC Industrial Transformation Research Hubs

  • 2021: $294,034
  • 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, 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 John Fouyaxis, Prof John Grundy, Dr Kit Huckvale, David Varley, Nicole Cockayne, Dr Leonard Hoon, Dr Tanya Petrovich, Matthew Macfarlane, Dr Anju Kissoon Curumsing, Dr Tom McClean, Prof Deborah Parker, Ms Sharon Grocott, Dr Scott Barnett, Mr Steven Strange, Prof Jean-Guy Schneider, A/Prof Carsten Rudolph, Prof Nilmini Wickramasinghe, Dr Jordan Vincent, Mr Fernando Escorcia, Dr Gnana Bharathy

  • 2020: $553,025
  • 2019: $378,745

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

  • 2021: $32,457
  • 2019: $30,681

Supervisions

Principal Supervisor
2020

Junyang Qiu

Thesis entitled: Data-Driven Android Malware Intelligence with Machine Learning through Static Analysis

Doctor of Philosophy (Information Technology), School of Information Technology

2019

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

2018

Dang Pham Hai Nguyen

Thesis entitled: Representation Learning in Complex Data via Pattern Discovery

Doctor of Philosophy (Information Technology), School of Information Technology

Associate Supervisor
2019

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

2018

Thanh Binh Nguyen

Thesis entitled: Making Sense of Pervasive Signals: a Machine Learning Approach

Doctor of Philosophy (Information Technology), School of Information Technology