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.
Vu Minh 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, multi-modal analysis, generative model, and semantic segmentation. His research has been published at top-tier venues such as CVPR, ACL, IJCV, EMNLP, 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 and large language models for multi-modality, computer vision, natural language processing, and medical image analysis. Here is my Google Scholar profile.
My area of research includes:
- Multi-modal Large Language Models.
- Visual foundational models for zero-shot / few-shot learning of medical imaging.
- Vision-language modeling for medical image classification and segmentation.
- Generative models for image synthesis.
- Continual learning of semantic segmentation.
- Knowledge distillation for efficient deep learning.
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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 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. Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, abs/2403.07636, 11492-11501.
2024 Phan, V. M. H., Xie, Y., Zhang, B., Qi, Y., Liao, Z., Perperidis, A., . . . To, M. S. (2024). Structural Attention: Rethinking Transformer for Unpaired Medical Image Synthesis. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 15007 LNCS, 690-700.
Scopus32023 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.
Scopus62023 Zhang, B., Liu, L., Phan, M. H., Tian, Z., Shen, C., & Liu, Y. (2023). SegViT v2: Exploring Efficient and Continual Semantic Segmentation with Plain Vision Transformers. International Journal of Computer Vision, 132(4), 1126-1147.
Scopus72022 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.
Scopus9 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.
Scopus6 -
Conference Papers
Year Citation 2024 Yuan, J., Phan, M. H., Liu, L., & Liu, Y. (2024). FAKD: Feature Augmented Knowledge Distillation for Semantic Segmentation. In Proceedings - 2024 IEEE Winter Conference on Applications of Computer Vision, WACV 2024 (pp. 584-594). Online: IEEE.
DOI Scopus62024 Liu, L., Wang, Z., Phan, M. H., Zhang, B., Ge, J., & Liu, Y. (2024). BPKD: Boundary Privileged Knowledge Distillation for Semantic Segmentation. In Proceedings - 2024 IEEE Winter Conference on Applications of Computer Vision, WACV 2024 (pp. 1051-1061). Waikoloa, HI, USA: IEEE.
DOI Scopus42024 Phan, V. M. H., Xie, Y., Zhang, B., Qi, Y., Liao, Z., Perperidis, A., . . . To, M. -S. (2024). Structural Attention: Rethinking Transformer for Unpaired Medical Image Synthesis.. In M. G. Linguraru, Q. Dou, A. Feragen, S. Giannarou, B. Glocker, K. Lekadir, & J. A. Schnabel (Eds.), MICCAI (7) Vol. 15007 (pp. 690-700). Marrakesh, Morocco: Springer. 2024 Chowdhury, T. F., Phan, V. M. H., Liao, K., To, M. -S., Xie, Y., Hengel, A. V. D., . . . Liao, Z. (2024). AdaCBM: An Adaptive Concept Bottleneck Model for Explainable and Accurate Diagnosis.. In M. G. Linguraru, Q. Dou, A. Feragen, S. Giannarou, B. Glocker, K. Lekadir, & J. A. Schnabel (Eds.), MICCAI (10) Vol. 15010 (pp. 35-45). Marrakesh, Morocco: Springer. 2024 Chowdhury, T. F., Liao, K., Phan, V. M. H., To, M. -S., Xie, Y., Hung, K., . . . Liao, Z. (2024). CAPE: CAM as a Probabilistic Ensemble for Enhanced DNN Interpretation.. In CVPR (pp. 11072-11081). Seattle, WA, USA: IEEE. 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.. In CVPR (pp. 11492-11501). Seattle, WA, USA: IEEE. 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.
DOI Scopus30 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.
DOI Scopus5 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.
DOI 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.
DOI Scopus2 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.
DOI Scopus188 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 Principal 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
