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 foundational models and multimodal learning for medical image analysis. His research interests include vision language models, generative AI, and universal models that are able to understand multi-modal inputs and perform diverse tasks. His research has been published at top-tier venues such as CVPR, ACL, EMNLP, IJCAI, WACV, MICCAI, IJCV, and Pattern Recognition. 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 2025 Ge, J., Zhang, B., Liu, A., Phan, V. M. H., Chen, Q., Shu, Y., & Zhao, Y. (2025). CIT: Rethinking class-incremental semantic segmentation with a Class Independent Transformation. Pattern Recognition, 167, 111707.
2023 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.
Scopus152022 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.
Scopus10 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 -
Book Chapters
Year Citation 2026 Liu, Y., Verjans, J., Phan, V. M. H., & Liao, Z. (2026). CA-Seg: An Attribute-Based Medical Image Segmentation Framework for Unified Out-of-Distribution Medical Image Segmentation. In Lecture Notes in Computer Science (pp. 17-31). Springer Nature Switzerland.
DOI -
Conference Papers
Year Citation 2025 Qi, X., Zhang, Z., Handoko, A. B., Zheng, H., Chen, M., Huy, T. D., . . . To, M. S. (2025). ProjectedEx: Enhancing Generation in Explainable AI for Prostate Cancer. In Proceedings IEEE Symposium on Computer Based Medical Systems (pp. 623-629). IEEE.
DOI2024 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 Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR 2024) (pp. 11492-11501). Seattle, WA, USA: Institute of Electrical and Electronics Engineers (IEEE).
DOI Scopus102024 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 Scopus132024 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 COMPUTER SOC.
DOI Scopus122024 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 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 Lecture Notes in Computer Science Vol. 15007 (pp. 690-700). Marrakesh, Morocco: Springer.
DOI Scopus72024 Nguyen, T. D., Huynh, T. T., Phan, M. H., Nguyen, Q. V. H., & Le Nguyen, P. (2024). CARER - ClinicAl Reasoning-Enhanced Representation for Temporal Health Risk Prediction. In EMNLP 2024 - 2024 Conference on Empirical Methods in Natural Language Processing, Proceedings of the Conference (pp. 10392-10407). Miami, Florida: Association for Computational Linguistics.
DOI2023 Phan, V. M. H., Liao, Z., Verjans, J. W., & To, M. -S. (2023). Structure-Preserving Synthesis: MaskGAN for Unpaired MR-CT Translation. In Lecture Notes in Computer Science Vol. 14229 LNCS (pp. 56-65). Vancouver, BC, Canada,: Springer Nature Switzerland.
DOI Scopus112022 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 Scopus44 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 Scopus6 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 Scopus221 WoS76 -
Preprint
Year Citation 2025 Huy, T. D., Tran, S. K., Nguyen, P., Tran, N. H., Sam, T. B., Hengel, A. V. D., . . . Phan, V. M. H. (2025). Interactive Medical Image Analysis with Concept-based Similarity
Reasoning.2025 Nguyen, D., Ho, M. K., Ta, H., Nguyen, T. T., Chen, Q., Rav, K., . . . Phan, V. M. H. (2025). Localizing Before Answering: A Hallucination Evaluation Benchmark for
Grounded Medical Multimodal LLMs.2025 Huy, T. D., Huynh, D. A., Xie, Y., Qi, Y., Chen, Q., Nguyen, P. L., . . . Phan, V. M. H. (2025). Seeing the Trees for the Forest: Rethinking Weakly-Supervised Medical
Visual Grounding.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
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