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. SPRINGER. 2019, Vol. 33, Issue 3, pp. 577-606. DOI: 10.1007/s10618-019-00615-5
  2. Demirović, E.; Stuckey, PJ.; Bailey, J.; Chan, J.; Leckie, C.; Ramamohanarao, K.; Guns, T. An Investigation into PredictionÂ�Â�Optimisation for the Knapsack Problem. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Springer International Publishing. 2019, Vol. 11494 LNCS, pp. 241-257. DOI: 10.1007/978-3-030-19212-9_16
  3. Srivastava, N.; Velloso, E.; Lodge, JM.; Erfani, S.; Bailey, J. Continuous evaluation of video lectures from real-time difficulty self-report. Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems - CHI '19. ACM Press. 2019. DOI: 10.1145/3290605.3300816
  4. Jia, Y.; Bailey, J.; Ramamohanarao, K.; Leckie, C.; Ma, X. Exploiting patterns to explain individual predictions. Knowledge and Information Systems. Springer Science and Business Media LLC. 2019. DOI: 10.1007/s10115-019-01368-9
  5. Moshtaghi, M.; Bezdek, JC.; Erfani, SM.; Leckie, C.; Bailey, J. Online cluster validity indices for performance monitoring of streaming data clustering. International Journal of Intelligent Systems. WILEY. 2019, Vol. 34, Issue 4, pp. 541-563. DOI: 10.1002/int.22064
  6. Ganji, M.; Chan, J.; Stuckey, PJ.; Bailey, J.; Leckie, C.; Ramamohanarao, K.; 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 International Publishing. 2019, Vol. 11052 LNAI, pp. 158-174. DOI: 10.1007/978-3-030-10928-8_10
  7. 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 Nature. 2018, Vol. 11013 LNAI, pp. 192-200. DOI: 10.1007/978-3-319-97310-4_22
  8. Ma, X.; Li, B.; Wang, Y.; M. Erfani, S.; Wijewickrema, S.; Schoenebeck, G.; Song, D.; Houle, ME.; Bailey, J. Characterizing Adversarial Subspaces Using Local Intrinsic Dimensionality. . ICLR. 2018.
  9. Wijewickrema, S.; Copson, B.; Ma, X.; Briggs, R.; Bailey, J.; Kennedy, G.; Oleary, S. Development and Validation of a Virtual Reality Tutor to Teach Clinically Oriented Surgical Anatomy of the Ear. 2018 IEEE 31st International Symposium on Computer-Based Medical Systems (CBMS). IEEE. 2018, Vol. 2018-June, pp. 12-17. DOI: 10.1109/CBMS.2018.00010
  10. Ma, X.; Wang, Y.; Houle, ME.; Zhou, S.; Erfani, SM.; Xia, S-T.; Wijewickrema, S.; Bailey, J. Dimensionality-Driven Learning with Noisy Labels. 35th International Conference on Machine Learning, ICML 2018. JMLR. 2018, Vol. 8, pp. 5332-5341.
  11. 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 SCIENCE. 2018, Vol. 13, Issue 1. DOI: 10.1371/journal.pone.0190611
  12. Ganji, M.; Chan, J.; Stuckey, PJ.; Bailey, J.; Leckie, C.; Ramamohanarao, K.; Davidson, I. Image constrained blockmodelling: A constraint programming approach. SIAM International Conference on Data Mining, SDM 2018. Society for Industrial and Applied Mathematics. 2018, pp. 19-27.
  13. 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. IEEE. 2018, pp. 8688-8696. DOI: 10.1109/CVPR.2018.00906
  14. 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, GK. Laboratory alerts to guide early intensive care team review in surgical patients: A feasibility, safety, and efficacy pilot randomized controlled trial. Resuscitation. ELSEVIER IRELAND LTD. 2018, Vol. 133, pp. 167-172. DOI: 10.1016/j.resuscitation.2018.10.012
  15. Ganj, M.; Bailey, J.; Stuckey, PJ. Lagrangian constrained community detection. 32nd AAAI Conference on Artificial Intelligence, AAAI 2018. AAAI. 2018, pp. 2983-2990.
  16. Wang, Y.; Dai, B.; Kong, L.; Erfani, SM.; 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, pp. 83-92.
  17. Zhou, S.; Erfani, S.; Bailey, J. Online CP Decomposition for Sparse Tensors. 2018 IEEE International Conference on Data Mining (ICDM). IEEE. 2018, Vol. 2018-November, pp. 1458-1463. DOI: 10.1109/ICDM.2018.00202
  18. 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.. The Journal of Laryngology & Otology. Cambridge University Press (CUP). 2018, Vol. 132, Issue 3, pp. 257-263. DOI: 10.1017/S0022215117002626
  19. 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 International Publishing. 2018, Vol. 10947 LNAI, pp. 584-598. DOI: 10.1007/978-3-319-93843-1_43
  20. 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 (IEEE). 2018, pp. 1-1. DOI: 10.1109/TCC.2018.2889956

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