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 - email supervisor to discuss availability.
Hieu Phan is a research fellow working on theoretical computer vision and deep learning models for medical imaging at AIML. His research interests include visual foundational models, vision language models, knowledge distillation, continual learning, and generative models for image synthesis. His research has been published at top-tier venues such as CVPR, ACL, IJCV, WACV, MICCAI, and Neurocomputing journal. He serves as a regular reviewer for TPAMI, IJCV, TCSVT, NeurIPS, and CVPR.
My research involves developing deep learning models for computer vision, medical image analysis, and natural language processing. Here is my Google Scholar profile.
My area of research includes:
- Visual foundational models for zero-shot / few-shot learning of medical imaging.
- Vision-language modelling for medical image classification and segmentation
- Continual learning of semantic segmentation
- Knowledge distillation for efficient deep learning
- Generative models for medical image synthesis
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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 -
Research Interests
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Journals
Year Citation 2024 Zhang, B., Liu, L., Phan, M. H., Tian, Z., Shen, C., & Liu, Y. (2024). SegViT v2: Exploring Efficient and Continual Semantic Segmentation with Plain Vision Transformers. International Journal of Computer Vision, 132(4), 1126-1147.
2023 Phan, V. M. H., Liao, Z., Verjans, J. W., & To, M. S. (2023). Structure-Preserving Synthesis: MaskGAN for Unpaired MR-CT Translation. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 14229 LNCS, 56-65.
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.
Scopus4 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.
Scopus3 -
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.
Scopus15 WoS52020 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.
Scopus4 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.
Scopus145 WoS76 -
Preprint
Year Citation 2024 Phan, V. M. H., Xie, Y., Qi, Y., Liu, L., Liu, L., Zhang, B., . . . Verjans, J. W. (2024). Decomposing Disease Descriptions for Enhanced Pathology Detection: A
Multi-Aspect Vision-Language Pre-training Framework.
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Current Higher Degree by Research Supervision (University of Adelaide)
Date Role Research Topic Program Degree Type Student Load Student Name 2024 Co-Supervisor Towards Explainable AI in Medical Imaging: Bridging the Gap between Deep Learning and Radiologist Trust with Human Interactions Doctor of Philosophy Doctorate Full Time Mr Huy Ta 2023 Co-Supervisor Explainable and Semantically Meaningful Deep Learning Models for Medical Risk Prediction and Diagnostics Doctor of Philosophy Doctorate Full Time Mr Townim Faisal Chowdhury
Connect With Me
External Profiles
