Dr Vu Minh Hieu Phan
Grant-Funded Researcher (B)
Australian Institute for Machine Learning - Projects
Faculty of Sciences, Engineering and Technology
Eligible to supervise Masters and PhD (as Co-Supervisor) - email supervisor to discuss availability.
Hieu Phan is a research fellow working on theoretical computer vision and deep learning models at AIML. His research interests include knowledge distillation, continual learning, and generative models for image synthesis. He also develops theoretical AI models for medical imaging tasks such as medical image synthesis and tumour segmentation. His research has been published at top-tier venues such as ACL, CVPR, MICCAI, and Neurocomputing journal. He serves as a regular reviewer for TPAMI, TCSVT IEEE Access, NeurIPS and CVPR.
My research involves developing artificial intelligence and machine learning for computer vision, medical image analysis and natural language processing, which includes semantic segmentation, knowledge distillation, continual learning and image to image translation. I also develop theoretical AI algorithms for medical imaging, which includes generative models for medical image synthesis and segmentation models for tumour contouring. My works have been published in top-tier AI venues in various fields, such as CVPR, MICCAI, ACL and Neurocomputing journal. I have served as a regular reviewer for TPAMI, TCSVT IEEE Access, NeuRIPS, and CVPR. Here is my Google Scholar profile.
-
Appointments
Date Position Institution name 2022 - ongoing Research Fellow Australian Institute of Machine Learning -
Education
Date Institution name Country Title University of Wollongong Australia Doctor of Philosphy
-
Journals
Year Citation 2022 Phan, M. H., Phung, S. L., Luu, K., & Bouzerdoum, A. (2022). Efficient hyperspectral image segmentation for biosecurity scanning using knowledge distillation from multi-head teacher. Neurocomputing, 504, 189-203.
Scopus3 WoS22021 Phan, M. H., Nguyen, Q., Phung, S. L., Zhang, W. E., Vo, T. D., & Sheng, Q. Z. (2021). CompactNet: A Light-Weight Deep Learning Framework for Smart Intrusive Load Monitoring. IEEE Sensors Journal, 21(22), 25181-25189.
Scopus1- Phan, M. H., Liao, Z., Verjans, J. W., & To, M. -S. (n.d.). Structure-Preserving Synthesis: MaskGAN for Unpaired MR-CT Translation. MICCAI 2023. -
Conference Papers
Year Citation 2022 Phan, M. H., Ta, T. -A., Phung, S. L., Tran-Thanh, L., & Bouzerdoum, A. (2022). Class Similarity Weighted Knowledge Distillation for Continual Semantic Segmentation. In 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Vol. 2022-June (pp. 16845-16854). Online: IEEE.
Scopus22020 Nguyen, V. K., Sheng, Q. Z., Mahmood, A., Zhang, W. E., Phan, M. H., & Vo, T. D. (2020). Demo abstract: an internet of plants system for micro gardens. In Proceedings of the 19th ACM/IEEE International Conference on Information Processing in Sensor Networks (IPSN 2020) (pp. 355-356). online: IEEE.
Scopus3 WoS12020 Nguyen, V. K., Phan, M. H., Zhang, W. E., Sheng, Q. Z., & Vo, T. D. (2020). A hybrid approach for intrusive appliance load monitoring in smart home. In Proceedings of the IEEE International Conference on Smart Internet of Things (SmartIoT 2020) (pp. 154-160). online: IEEE.
Scopus32020 Phan, M. H., Phung, S. L., & Bouzerdoum, A. (2020). Ordinal depth classification using region-based self-attention. In Proceedings of ICPR 2020 25th International Conference on Pattern Recognition (pp. 3620-3627). New York, NY, USA: IEEE.
Scopus1 WoS12020 Phan, M. H., & Ogunbona, P. O. (2020). Modelling Context and Syntactical Features for Aspect-based Sentiment Analysis. In D. Jurafsky, J. Chai, N. Schluter, & J. Tetreault (Eds.), Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics (pp. 3211-3220). Stroudsburg PA, USA: Association for Computational Linguistics.
Scopus109 WoS72
Connect With Me
External Profiles
