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Dr Truyen Tran

STAFF PROFILE

Position

Lecturer In Computer Networks

Faculty

Faculty of Sci Eng & Built Env

Department

School of Info Technology

Campus

Geelong Waurn Ponds Campus

Qualifications

Bachelor of Science, University of Melbourne, 2001
Postgraduate Diploma in Science, Curtin University, 2005
Doctor of Philosophy, Curtin University, 2008
Graduate Certificate of Higher Education, Deakin University, 2016

Biography summary

Truyen Tran is a lecturer at Deakin University. He is member of Centre for Pattern Recognition and Data Analytics (PRaDA) where he leads the work on deep learning, healthcare analytics and software analytics. His other research topics include probabilistic graphical models, recommender systems, learning to rank, anomaly detection, multi-relational databases, model stability, and mixed-type analysis. He publishes regularly in top venues such as CVPR, NIPS, UAI, AAAI, KDD, ICML, PAKDD, and ACML. Tran has received multiple recognition, awards and prizes including Best Paper Runner Up at UAI (2009), Geelong Tech Award (2013), CRESP Best Paper of the Year (2014), Third Prize on Kaggle Galaxy-Zoo Challenge (2014), Title of Kaggle Master (2014), Best Student Paper Runner Up at PAKDD (2015), Distinguished Paper at ACM SIGSOFT (2015), and Deakin Thought Leader (2016). He obtained a Bachelor of Science from University of Melbourne and a PhD in Computer Science from Curtin University in 2001 and 2008, respectively. He spent 3 years at Curtin University before moving to Deakin in 2012.

Research interests

Artificial intelligence

Data science

Biomedical informatics

Teaching interests

Machine learning

Data science

Healthcare analytics

Knowledge areas

Machine learning

Data mining

Artificial intelligence

Healthcare analytics

Biomedical informatics

Recommender systems

Data science

Awards

2015: PAKDD'15 Best student paper runner-up
2015: ACM  SIGSOFT Distinguished Paper Award.
2014: CRESP Best paper ward
2014: Team third prize in the Galaxy Zoo challenge
2013: Team best tech ward in Geelong
2009: UAI'09 Best paper runner-up

Publications

Filter by

2016

Modelling human preferences for ranking and collaborative filtering: a probabilistic ordered partition approach

Dr Truyen Tran, Prof Dinh Phung, Prof Svetha Venkatesh

(2016), Vol. 47, pp. 157-188, Knowledge and information systems, New York, N.Y., C1

journal

Preference relation-based markov random fields

Mr Shaowu Liu, A/Prof Gang Li, Dr Truyen Tran, Jiang Yuan

(2016), pp. 1-16, ACML 2015 : Proceedings of 7th Asian Conference on Machine Learning, Hong Kong, E1

conference

DeepCare: a deep dynamic memory model for predictive medicine

Ms Trang Thi Minh Pham, Dr Truyen Tran, Prof Dinh Phung, Prof Svetha Venkatesh

(2016), pp. 30-41, Advances in knowledge discovery and data mining : 19th Pacific-Asia Conference, PAKDD 2015, Ho Chi Minh City, Vietnam, May 19-22, 2015, proceedings, New York, N.Y., B1

chapter

Graph-induced restricted Boltzmann machines for document modeling

Dr Tu Nguyen, Dr Truyen Tran, Prof Dinh Phung, Prof Svetha Venkatesh

(2016), Vol. 328, pp. 60-75, Information sciences, Amsterdam, The Netherlands, C1

journal

Consistency of the Health of the Nation Outcome Scales (HoNOS) at inpatient-to-community transition

Dr Wei Luo, A/Prof Richard Harvey, Dr Truyen Tran, Prof Dinh Phung, Prof Svetha Venkatesh, A/Prof Jason Connor

(2016), Vol. 6, pp. 1-6, BMJ open, London, Eng., C1

journal

Neural choice by elimination via highway networks

Dr Truyen Tran, Prof Dinh Phung, Prof Svetha Venkatesh

(2016), pp. 15-25, Trends and applications in knowledge discovery and data mining: PAKDD 2016 Workshops, BDM, MLSDA, PACC, WDMBF, Auckland, New Zealand, April 19, 2016, revised selected papers, Cham, Switzerland, B1

chapter

Screening for post 32-week preterm birth risk: how helpful is routine perinatal data collection?

Dr Wei Luo, Miss Emily Huning, Dr Truyen Tran, Prof Dinh Phung, Prof Svetha 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

Mr Shivapratap Gopakumar, Dr Truyen Tran, Dr Wei Luo, Dinh Phung, Prof Svetha Venkatesh

(2016), Vol. 4, pp. 1-16, JMIR medical informatics, Toronto, Ont., C1

journal

Collaborative filtering via sparse Markov random fields

Dr Truyen Tran, Dinh Phung, Prof Svetha Venkatesh

(2016), Vol. 369, pp. 221-237, Information sciences, Amsterdam, The Netherlands, C1

journal

Preterm birth prediction : deriving stable and interpretable rules from high dimensional data

Dr Truyen Tran, Dr Wei Luo, Prof Dinh Phung, Prof Jonathan Morris, Kristen Rickard, Prof Svetha Venkatesh

(2016), pp. 1-13, MLHC 2016 : Proceedings on Conference on Machine Learning in Healthcare, Los Angeles, Calif., E1

conference

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

Dr Chandan Karmakar, Dr Wei Luo, Dr Truyen Tran, Prof Michael Berk, Prof Svetha Venkatesh

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

journal

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

Dr Wei Luo, Prof Dinh Phung, Dr Truyen Tran, Dr Sunil Gupta, Dr Santu Rana, Dr Chandan Karmakar, Dr Alistair Shilton, Prof John Yearwood, Nevenka Dimitrova, Tu Bao Ho, Prof Svetha Venkatesh, Prof Michael Berk

(2016), Vol. 18, pp. 1-10, Journal of medical internet research, Toronto, Ont., C1

journal

DeepSoft: a vision for a deep model of software

Hoa Dam, Dr Truyen Tran, Prof John Grundy, Aditya Ghose

(2016), pp. 944-947, FSE 2016: Proceedings of the 24th ACM SIGSOFT International Symposium on Foundations of Software Engineering, New York, N.Y., E1

conference
2015

Stabilized sparse ordinal regression for medical risk stratification

Dr Truyen Tran, Prof Dinh Phung, Dr Wei Luo, Prof Svetha Venkatesh

(2015), Vol. 43, pp. 555-582, Knowledge and information systems: an international journal, Berlin, Germany, C1

journal

Characterization and prediction of issue-related risks in software projects

Morakot Choetkiertikul, Hoa Dam, Dr Truyen Tran, Aditya Ghose

(2015), pp. 280-291, MSR 2015 : Proceedings of the 12th Working Conference on Mining Software Repositories, Piscataway, N.J., E1

conference

Stabilizing high-dimensional prediction models using feature graphs

Mr Shivapratap Gopakumar, Dr Truyen Tran, Dr Tu Nguyen, Prof Dinh Phung, Prof Svetha Venkatesh

(2015), Vol. 19, pp. 1044-1052, IEEE journal of biomedical and health informatics, Champaign, III., C1

journal

Tensor-variate restricted Boltzmann machines

Dr Tu Nguyen, Dr Truyen Tran, Prof Dinh Phung, Prof Svetha Venkatesh

(2015), pp. 2887-2893, AAAI 2015: The Proceedings of the 29th AAAI Conference on Artificial Intelligence, Palo Alto, Calif., E1

conference

Learning vector representation of medical objects via EMR-driven nonnegative restricted Boltzmann machines (eNRBM)

Dr Truyen Tran, Dr Tu Nguyen, Prof Dinh Phung, Prof Svetha Venkatesh

(2015), Vol. 54, pp. 96-105, Journal of biomedical informatics, Amsterdam, The Netherlands, C1

journal

Stabilizing sparse cox model using statistic and semantic structures in electronic medical records

Mr Shivapratap Gopakumar, Dr Tu Nguyen, Dr Truyen Tran, Prof Dinh Phung, Prof Svetha Venkatesh

(2015), pp. 331-343, Advances in knowledge discovery and data mining 19th Pacific-Asia Conference, PAKDD 2015, Ho Chi Minh City, Vietnam, May 19-22, 2015, Proceedings, Part II, Berlin, Germany, B1

chapter

Predicting delays in software projects using networked classification

Morakot Choetkiertikul, Dr Hoa Khanh Dam, Dr Truyen Tran, Aditya Ghose

(2015), pp. 353-364, ASE 2015 : Proceedings of the 30th IEEE/ACM International Conference on Automated Software Engineering, Piscataway, N.J., E1

conference

Who will answer my question on Stack Overflow?

Morakot Choetkiertikul, Daniel Avery, Dr Hoa Khanh Dam, Dr Truyen Tran, Aditya Ghose

(2015), pp. 155-164, ASWEC 2015 : Proceedings of the 24th Australasian Software Engineering Conference, Piscataway, N.J., E1

conference

Web search activity data accurately predict population chronic disease risk in the USA

Dr Thin Nguyen, Dr Truyen Tran, Dr Wei Luo, Dr Sunil Gupta, Dr Santu Rana, Prof Dinh Phung, Dr Melanie Nichols, Dr Lynne Millar, Prof Svetha Venkatesh, Prof Steven 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

Dr Wei Luo, Dr Thin Nguyen, Dr Melanie Nichols, Dr Truyen Tran, Dr Santu Rana, Dr Sunil Gupta, Prof Dinh Phung, Prof Svetha Venkatesh, Prof Steven Allender

(2015), Vol. 10, pp. 1-13, PLoS One, San Francisco, Calif., C1

journal
2014

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

Dr Santu Rana, Dr Truyen Tran, Dr Wei Luo, Prof Dinh Phung, Richard L. Kennedy, Prof Svetha Venkatesh

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

journal

Ipoll: Automatic polling using online search

Dr Thin Nguyen, Prof Dinh Phung, Dr Wei Luo, Dr Truyen Tran, Prof Svetha Venkatesh

(2014), pp. 266-275, Web information system engineering - WISE 2014, Berlin, Germany, B1

chapter

Tree-based iterated local search for Markov random fields with applications in image analysis

Dr Truyen Tran, Prof Dinh Phung, Prof Svetha Venkatesh

(2014), Vol. 21, pp. 25-45, Journal of heuristics, Berlin, Germany, C1

journal

Ordinal random fields for recommender systems

Mr Shaowu Liu, Dr Truyen Tran, A/Prof Gang Li, Yuan Jiang

(2014), pp. 283-298, ACML 2014: Proceedings of the Sixth Asian Conference on Machine Learning, Nha Trang, Vietnam, E1

conference

Speed up health research through topic modeling of coded clinical data

Dr Wei Luo, Prof Dinh Phung, Dr Vu Nguyen, Dr Truyen Tran, Prof Svetha Venkatesh

(2014), pp. 1-4, IAPR 2014: Proceedings of 2nd International Workshop on Pattern Recognition for Healthcare Analytics, Stockholm, Sweden, E1-1

conference

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

Dr Truyen Tran, Dr Wei Luo, Prof Dinh Phung, A/Prof Richard Harvey, Prof Michael Berk, Richard L. Kennedy, Prof Svetha Venkatesh

(2014), Vol. 14, pp. 1-9, BMC Psychiatry, London, England, C1

journal

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

Dr Sunil Gupta, Dr Truyen Tran, Dr Wei Luo, Prof Dinh Phung, Richard L. Kennedy, Adam Broad, David Campbell, David Kipp, Madhu Singh, Dr Mustafa Khasraw, Leigh Matheson, Prof David Ashley, Prof Svetha Venkatesh

(2014), Vol. 4, pp. 1-7, BMJ open, London, England, C1

journal

A framework for feature extraction from hospital medical data with applications in risk prediction

Dr Truyen Tran, Dr Wei Luo, Prof Dinh Phung, Dr Sunil Gupta, Dr Santu Rana, Mr Richard Kennedy, Ann Larkins, Prof Svetha Venkatesh

(2014), Vol. 15, pp. 1-9, BMC Bioinformatics, London,Eng., C1

journal
2013

Learning sparse latent representation and distance metric for image retrieval

Dr Tu Nguyen, Dr Truyen Tran, Prof Dinh Phung, Prof Svetha Venkatesh

(2013), pp. 1-6, ICME 2013 : Proceedings of the 14th IEEE International Conference on Multimedia and Expo, Piscataway, N.J., E1

conference

Latent patient profile modelling and applications with mixed-variate restricted Boltzmann machine

Dr Tu Nguyen, Dr Truyen Tran, Prof Dinh Phung, Prof Svetha Venkatesh

(2013), pp. 123-135, PAKDD 2013 : Advances in knowledge discovery and data mining : Proceedings of the 17th Pacific-Asia Conference, Berlin, Germany, E1

conference

An integrated framework for suicide risk prediction

Dr Truyen Tran, Prof Dinh Phung, Dr Wei Luo, A/Prof Richard Harvey, Prof Michael Berk, Prof Svetha Venkatesh

(2013), pp. 1410-1418, KDD'13: Proceedings of the 19th ACM SIGKDD international conference on Knowledge discovery and data mining, New York, N.Y., E1-1

conference

Thurstonian Boltzmann machines: learning from multiple inequalities

Dr Truyen Tran, Prof Dinh Phung, Prof Svetha Venkatesh

(2013), pp. 46-54, ICML 2013 : Proceedings of the Machine Learning 2013 International Conference, Atlanta, Ga., E1-1

conference
2012

Cumulative restricted Boltzmann machines for ordinal matrix data analysis

Dr Truyen Tran, Prof Dinh Phung, Prof Svetha Venkatesh

(2012), pp. 411-426, ACML 2012 : Proceedings of the 4th Asian Conference on Machine Learning, Singapore, E1

conference

Learning from ordered sets and applications in collaborative ranking

Dr Truyen Tran, Prof Dinh Phung, Prof Svetha Venkatesh

(2012), pp. 427-442, ACML 2012 : Proceedings of the 4th Asian Conference on Machine Learning, Singapore, E1

conference

Learning Boltzmann distance metric for face recognition

Dr Truyen Tran, Prof Dinh Phung, Prof Svetha Venkatesh

(2012), pp. 218-223, ICME 2012 : Proceedings of the 13th IEEE International Conference on Multimedia and Expo, Piscataway, N.J., E1

conference

A sequential decision approach to ordinal preferences in recommender systems

Dr Truyen Tran, Prof Dinh Phung, Prof Svetha Venkatesh

(2012), pp. 676-682, AAAI 2012 : Proceedings of the 26th National Conference on Artificial Intelligence, Toronto, Ont., E1

conference

Embedded restricted Boltzmann machines for fusion of mixed data types and applications in social measurements analysis

Dr Truyen Tran, Prof Dinh Phung, Prof Svetha Venkatesh

(2012), pp. 1814-1821, FUSION 2012 : Proceedings of the 15th International Conference on Information Fusion, Melbourne, Vic., E1

conference
2011

Mixed-variate restricted Boltzmann machines

Dr Truyen Tran, Prof Dinh Phung, Prof Svetha Venkatesh

(2011), pp. 213-229, ACML 2011 : Proceedings of the 3rd Asian Conference on Machine Learning, Taoyuan, Taiwan, E1-1

conference

Probabilistic models over ordered partitions with applications in document ranking and collaborative filtering

Dr Truyen Tran, Prof Dinh Phung, Prof Svetha Venkatesh

(2011), pp. 426-437, SDM 2011 : Proceedings of the 11th SIAM International Conference on Data Mining, Philadelphia, Pa., E1-1

conference
2010

Hyper-community detection in the blogosphere

Dr Thin Nguyen, Prof Dinh Phung, Brett Adams, Dr Truyen Tran, Prof Svetha Venkatesh

(2010), pp. 21-26, WSM 2010 : Proceedings of the 2nd ACM SIGMM Workshop on Social Media, New York, N. Y., E1-1

conference

Nonnegative shared subspace learning and its application to social media retrieval

Dr Sunil Gupta, Prof Dinh Phung, Brett Adams, Dr Truyen Tran, Prof Svetha Venkatesh

(2010), pp. 1169-1178, KDD 2010 : Proceedings of the 16th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, New York, N. Y., E1-1

conference

Classification and pattern discovery of mood in weblogs

Dr Thin Nguyen, Prof Dinh Phung, Brett Adams, Dr Truyen Tran, Prof Svetha Venkatesh

(2010), pp. 283-290, Advances in knowledge discovery and data mining : 14th Pacific-Asia Conference, PAKDD 2010, Hyderabad, India, June 21-24, 2010 ; proceedings. part II, Berlin, Germany, E1-1

conference
2009

Ordinal Boltzmann machines for collaborative filtering

Dr Truyen Tran, Prof Dinh Phung, Prof Svetha Venkatesh

(2009), pp. 548-556, UAI 2009 : Proceedings of the 25th Conference on Uncertainty in Artificial Intelligence, Arlington, Va., E1-1

conference
2008

Learning discriminative sequence models from partially labelled data for activity recognition

Dr Truyen Tran, Hung Bui, Prof Dinh Phung, Prof Svetha Venkatesh

(2008), pp. 903-912, PRICAI 2008 : trends in artificial intelligence : 10th Pacific Rim International Conference on Artificial Intelligence, Hanoi, Vietnam, December 15-19, 2008, proceedings, Berlin, Germany, E1-1

conference

Constrained sequence classification for lexical disambiguation

Dr Truyen Tran, Prof Dinh Phung, Prof Svetha Venkatesh

(2008), pp. 430-441, PRICAI 2008 : trends in artificial intelligence : 10th Pacific Rim International Conference on Artificial Intelligence, Hanoi, Vietnam, December 15-19, 2008, proceedings, Berlin, Germany, E1-1

conference

Hierarchical semi-markov conditional random fields for recursive sequential data

Dr Truyen Tran, Prof Dinh Phung, Hung Bui, Prof Svetha Venkatesh

(2008), pp. 1657-1664, NIPS 2008 : Advances in Neural Information Processing Systems 21 : Proceedings of the 2008 Conference, Red Hook, N. Y., E1-1

conference
2007

Preference networks : probabilistic models for recommendation systems

Dr Truyen Tran, Prof Dinh Phung, Prof Svetha Venkatesh

(2007), pp. 191-198, Data Mining and Analytics 2007 : Proceedings of the Sixth Australasian Data Mining Conference - AusDM 2007, Sydney, N. S. W., E1-1

conference

Preference Networks: probabilistic models for recommendation systems

Dr Truyen Tran, Prof Dinh Phung, Prof Svetha Venkatesh

(2007), pp. 195-202, Proc. of 6th Australasian Data Mining Conference: AusDM 2007, Gold Coast, N.S.W., E1-1

conference
2006

AdaBoost.MRF: boosted Markov random forests and application to multilevel activity recognition

Dr Truyen Tran, Prof Dinh Phung, Hung Bui, Prof Svetha Venkatesh

(2006), pp. 1686-1693, CVPR 2006 : Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, Piscataway, N.J., E1-1

conference
2005

Boosted Markov networks for activity recognition

Dr Truyen Tran, Hung Bui, Prof Svetha Venkatesh

(2005), pp. 289-294, Proceedings of the 2005 Intelligent Sensors, Sensor Networks & Information Processing Conference, Piscataway, N.J., E1-1

conference

Human activity learning and segmentation using partially hidden discriminative models

Dr Truyen Tran, Hung Bui, Prof Svetha Venkatesh

(2005), pp. 87-95, HAREM 2005 : Proceedings of the International Workshop on Human Activity Recognition and Modelling, Oxford, U. K., E1-1

conference

Grants

Industry and Other Funding

Predicting software components containing safety hazards using deep learning

Dr Hoa Khanh Dam, Prof Aditya Ghose, Dr Truyen Tran, Prof John Grundy

  • 2017: $31,490

Supervisions

Associate Supervisor
2016

Xin Zhang

Thesis entitled: Sparse representation for face images

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

2015

Tu Dinh Nguyen

Thesis entitled: Structured representation learning from complex data

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