Dr Wei Luo

STAFF PROFILE

Position

Lecturer In Information Technology

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

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

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
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
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

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

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

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

chapter

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

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

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

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

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

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

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

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

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

chapter

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

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

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

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

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

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

chapter

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

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, Berlin, Germany, C1

journal

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

journal

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), pp. 135-148, PAKDD 2011 : Advances in Knowledge Discovery and Data Mining : Proceedings of PAKDD 2011, Shenzhen, China, E1-1

conference
2010

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

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

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

journal
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, CIDM 2009 : Proceedings of the 2009 IEEE Symposium on Computational Intelligence and Data Mining, Nashville, Tennesee, E1-1

conference
2007

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

conference
2006

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, Que?bec, Canada, June 7-9, 2006 : proceedings, Quebec City, Quebec, E1-1

conference

Mind change efficient learning

W Luo, O Schulte

(2006), Vol. 204, pp. 989-1011, Information and computation, Amsterdam, The Netherlands, C1-1

journal
2005

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

conference

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

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, A/Prof Liliana Orellana, Dr Wei Luo, A/Prof Kylie Hesketh, Dr Denise Wilfley

NHMRC Project Grant

  • 2018: $223,204
  • 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 Rafael Calvo, Prof Helen Christensen, Prof Patricia Williams, Prof Dinh Phung, 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 John Hansen, Prof James Warren, Dr Roopak Sinha, Prof A Smeaton, Mr Ian Aitken, Mr Fonda Voukelatos, Mr Jeffrey Fiebig, Mr Dean Serroni, Mr Christopher Farguhar, Ms Jennifer Biggin, Mr John Fouyaxis, Mr Kevin Hoon, Prof John Grundy, Dr Leonard Hoon, David Varley

ARC Industrial Transformation Research Hubs

  • 2018: $253,606
  • 2017: $601,698

Industry and Other Funding

Unlocking factors for successful job placement through machine learning

Prof Svetha Venkatesh, Dr Wei Luo

  • 2018: $52,019
  • 2017: $78,028

Supervisions

Associate Supervisor
2018

Thanh Binh Nguyen

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

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