Professor James Bailey

  • Room: Level: 07 Room: 7.09
  • Building: Doug McDonell Building
  • Campus: Parkville

Research interests

  • Artificial intelligence
  • Data mining
  • Health informatics
  • Immersive Simulation
  • Learning Analytics
  • Machine learning

Personal webpage

http://people.eng.unimelb.edu.au/baileyj/

Biography

James Bailey is a Professor in the School of Computing and Information Systems, The University of Melbourne, and has been an Australian Research Council Future Fellow. He is a researcher and educator in machine learning, artificial intelligence and data science.

Recent publications

  1. Naderivesal S, Kulik L, Bailey J. An effective and versatile distance measure for spatiotemporal trajectories. Data Mining and Knowledge Discovery. Kluwer Academic Publishers. 2019. DOI: 10.1007/s10618-019-00615-5
  2. Moshtaghi M, Bezdek J, Monazam Erfani S, Leckie C, Bailey J. Online cluster validity indices for performance monitoring of streaming data clustering. INTERNATIONAL JOURNAL OF INTELLIGENT SYSTEMS. John Wiley & Sons. 2019, Vol. 34, Issue 4. DOI: 10.1002/int.22064
  3. Ganji M, Chan J, Stuckey PJ, Bailey J, Leckie C, Kotagiri R, Park L. Semi-supervised blockmodelling with pairwise guidance. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Springer Verlag. 2019, Vol. 11052 LNAI. DOI: 10.1007/978-3-030-10928-8_10
  4. Mirmomeni M, Kowsar Y, Kulik L, Bailey J. An automated matrix profile for mining consecutive repeats in time series. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Springer Verlag. 2018, Vol. 11013 LNAI. DOI: 10.1007/978-3-319-97310-4_22
  5. Zhou Y, Wijewickrema S, Ioannou I, Bailey J, Kennedy G, Nestel D, O'Leary S. Do experts practice what they profess?. PLOS ONE. Public Library of Science. 2018, Vol. 13, Issue 1. DOI: 10.1371/journal.pone.0190611
  6. Ganji M, Chan J, Stuckey P, Bailey J, Leckie C, Kotagiri R, Davidson I. Image constrained blockmodelling: A constraint programming approach. SIAM International Conference on Data Mining, SDM 2018. 2018.
  7. Wang Y, Liu W, Ma X, Bailey J, Zha H, Song L, Xia S-T. Iterative Learning with Open-set Noisy Labels. 2018 IEEE/CVF CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION (CVPR). IEEE Computer Society. 2018. DOI: 10.1109/CVPR.2018.00906
  8. Bellomo R, Chan M, Guy C, Proimos H, Franceschi F, Crisman M, Nadkarni A, Ancona P, Pan K, Di Muzio F, Presello B, Bailey J, Young M, Hart G. Laboratory alerts to guide early intensive care team review in surgical patients: A feasibility, safety, and efficacy pilot randomized controlled trial. RESUSCITATION. Elsevier Science Ireland. 2018, Vol. 133. DOI: 10.1016/j.resuscitation.2018.10.012
  9. Ganj M, Bailey J, Stuckey P. Lagrangian constrained community detection. 32nd AAAI Conference on Artificial Intelligence, AAAI 2018. 2018.
  10. Wang Y, Dai B, Kong L, Monazam Erfani S, Bailey J, Zha H. Learning deep hidden nonlinear dynamics from aggregate data. 34th Conference on Uncertainty in Artificial Intelligence 2018, UAI 2018. 2018, Vol. 1.
  11. Zhou S, Monazam Erfani S, Bailey J. Online CP Decomposition for Sparse Tensors. 18th IEEE International Conference on Data Mining Workshops (ICDMW). IEEE. 2018, Vol. 2018-November. DOI: 10.1109/ICDM.2018.00202
  12. Wijewickrema S, Zhou Y, Ioannou I, Copson B, Piromchai P, Yu C, Briggs R, Bailey J, Kennedy G, O'Leary S. Presentation of automated procedural guidance in surgical simulation: Results of two randomised controlled trials. Journal of Laryngology and Otology. Headley Brothers Invicta Press. 2018, Vol. 132, Issue 3. DOI: 10.1017/S0022215117002626
  13. Wijewickrema S, Ma X, Piromchai P, Briggs R, Bailey J, Kennedy G, O’leary S. Providing automated real-time technical feedback for virtual reality based surgical training: Is the simpler the better?. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Springer Verlag. 2018, Vol. 10947 LNAI. DOI: 10.1007/978-3-319-93843-1_43
  14. Zhao Y, Calheiros R, Gange G, Bailey J, Sinnott R. SLA-Based Profit Optimization Resource Scheduling for Big Data Analytics-as-a-Service Platforms in Cloud Computing Environments. IEEE Transactions on Cloud Computing. Institute of Electrical and Electronics Engineers. 2018. DOI: 10.1109/TCC.2018.2889956
  15. Romano S, Nguyen X, Verspoor C, Bailey J. The randomized information coefficient: assessing dependencies in noisy data. MACHINE LEARNING. Kluwer Academic Publishers. 2018, Vol. 107, Issue 3. DOI: 10.1007/s10994-017-5664-2

View a full list of publications on the University of Melbourne’s ‘Find An Expert’ profile