Zhibin Liao

Dr Zhibin Liao

Grant-Funded Researcher (C)

Australian Institute for Machine Learning - Projects

Faculty of Sciences, Engineering and Technology

Eligible to supervise Masters and PhD, but is currently at capacity - email supervisor to discuss availability.

Dr Zhibin Liao is a Senior Research Fellow at AIML. He has over 10 years of research experience in AI research and 6 years dedicated to medical AI. He has 35 publications and 2 US patents and was awarded over $3 million in funding as chief or co-investigator. His research interest is to develop AI solutions for solving clinical problems.

In 2021-2023 at AIML, he was the AI lead in an NHMRC partnership project RAPIDx AI, working with Siemens and SA Health to develop and clinically test a real-time myocardial injury detection AI. The AI is currently trialled at 6 South Australian hospitals with more than 17,000 enrolled patients.

From 2017 to 2019 at the University of British Columbia (Canada), he was a postdoctoral research fellow at the RCL Lab supervised by Professor Purang Abolmeasumi. He participated in an ultrasound cardiovascular diagnostic AI tool development during that period.

Dr Liao obtained a PhD in Computer Science at the University of Adelaide in 2018. During his PhD, he was a member of the Australian Research Council Centre of Excellence for Robotic Vision (ACRV). His PhD supervisor was Professor Gustavo Carneiro.

  • Appointments
    Date Position Institution name
    2022 - ongoing Senior Research Fellow University of Adelaide
    2019 - 2021 Postdoctoral Resaerch Fellow University of Adelaide
    2017 - 2019 Postdoctoral Research Fellow University of Birtish Columbia

  • Education
    Date Institution name Country Title
    2013 - 2018 University of Adelaide Australia PhD in Computer Science
    2012 - 2013 University of Adelaide Australia Bachelor in Computer Science (First Class Honours)
    2009 - 2012 University of Adelaide Australia Bachelor of Computer Science

  • Journals
    Year Citation
    2024 Saad, F. H., Farook, T. H., Ahmed, S., Zhao, Y., Liao, Z., Verjans, J. W., & Dudley, J. (2024). Facial and mandibular landmark tracking with habitual head posture estimation using linear and fiducial markers. Healthcare Technology Letters, 11(1), 21-30.
    DOI
    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.. CoRR, abs/2403.07636.
    2023 Luong, C. L., Behnami, D., Liao, Z., Yeung, D. F., Tsang, M. Y. C., Van Woudenberg, N., . . . Tsang, T. S. M. (2023). Machine learning derived echocardiographic image quality in patients with left ventricular systolic dysfunction: insights on the echo views of greatest image quality.. Int J Cardiovasc Imaging, 39(7), 1313-1321.
    DOI Scopus1 Europe PMC1
    2023 Prijs, J., Liao, Z., To, M. -S., Verjans, J., Jutte, P. C., Stirler, V., . . . Machine Learning Consortium. (2023). Development and external validation of automated detection, classification, and localization of ankle fractures: inside the black box of a convolutional neural network (CNN).. European journal of trauma and emergency surgery : official publication of the European Trauma Society, 49(2), 1057-1069.
    DOI Scopus8 WoS1 Europe PMC4
    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.
    DOI
    2022 Prijs, J., Liao, Z., Ashkani-Esfahani, S., Olczak, J., Gordon, M., Jayakumar, P., . . . Doornberg, J. N. (2022). Erratum: Artificial intelligence and computer vision in orthopaedic trauma: the why, how, and what (Bone Joint J. (2022) 104-B: 8 (911–914) DOI: 10.1302/0301-620X.104B8.BJJ-2022-0119.R1). Bone and Joint Journal, 104-B(10), 1189.
    DOI
    2022 Liao, Z., Liao, K., Shen, H., Van Boxel, M. F., Prijs, J., Jaarsma, R. L., . . . Verjans, J. W. (2022). CNN Attention Guidance for Improved Orthopedics Radiographic Fracture Classification.. IEEE J Biomed Health Inform, 26(7), 3139-3150.
    DOI Scopus5
    2022 Prijs, J., Liao, Z., Ashkani-Esfahani, S., Olczak, J., Gordon, M., Jayakumar, P., . . . Doornberg, J. N. (2022). Artificial intelligence and computer vision in orthopaedic trauma : the why, what, and how. The bone & joint journal, 104-B(8), 911-914.
    DOI Scopus8 Europe PMC2
    2021 Xie, Y., Zhang, J., Liao, Z., Verjans, J., Shen, C., & Xia, Y. (2021). Intra- and Inter-pair Consistency for Semi-supervised Gland Segmentation.. IEEE transactions on image processing : a publication of the IEEE Signal Processing Society, 31, 894-905.
    DOI Scopus14 WoS5 Europe PMC1
    2021 Luong, C., Liao, Z., Abdi, A., Girgis, H., Rohling, R., Gin, K., . . . Tsang, T. S. M. (2021). Automated estimation of echocardiogram image quality in hospitalized patients. International Journal of Cardiovascular Imaging, 37(1), 229-239.
    DOI Scopus10 Europe PMC4
    2021 Zhang, J., Xie, Y., Pang, G., Liao, Z., Verjans, J., Li, W., . . . Xia, Y. (2021). Viral pneumonia screening on chest X-rays using confidence-aware anomaly detection. IEEE Transactions on Medical Imaging, 40(3), 879-890.
    DOI Scopus180 WoS106 Europe PMC105
    2020 Liao, Z., Drummond, T., Reid, I., & Carneiro, G. (2020). Approximate Fisher information matrix to characterise the training of deep neural networks. IEEE Transactions on Pattern Analysis and Machine Intelligence, 42(1), 15-26.
    DOI Scopus12 WoS11
    2020 Liao, Z., Girgis, H., Abdi, A., Vaseli, H., Hetherington, J., Rohling, R., . . . Abolmaesumi, P. (2020). On Modelling Label Uncertainty in Deep Neural Networks: Automatic Estimation of Intra- Observer Variability in 2D Echocardiography Quality Assessment. IEEE Transactions on Medical Imaging, 39(6), 1868-1883.
    DOI Scopus26 Europe PMC7
    2019 Jafari, M. H., Girgis, H., Van Woudenberg, N., Liao, Z., Rohling, R., Gin, K., . . . Tsang, T. (2019). Automatic biplane left ventricular ejection fraction estimation with mobile point-of-care ultrasound using multi-task learning and adversarial training. International Journal of Computer Assisted Radiology and Surgery, 14(6), 1027-1037.
    DOI Scopus39 Europe PMC12
    2019 Dezaki, F. T., Liao, Z., Luong, C., Girgis, H., Dhungel, N., Abdi, A. H., . . . Tsang, T. (2019). Cardiac Phase Detection in Echocardiograms with Densely Gated Recurrent Neural Networks and Global Extrema Loss. IEEE Transactions on Medical Imaging, 38(8), 1821-1832.
    DOI Scopus56 Europe PMC7
    2017 Liao, Z., & Carneiro, G. (2017). A deep convolutional neural network module that promotes competition of multiple-size filters. Pattern Recognition, 71, 94-105.
    DOI Scopus23 WoS21

  • Book Chapters
    Year Citation
    2023 Liao, Z., van den Hengel, A., & Verjans, J. W. (2023). Medical visual question answering. In A. C. Chang, A. Limon, R. Brisk, F. Lopez-Jimenez, & L. Y. Sun (Eds.), Intelligence-Based Cardiology and Cardiac Surgery: Artificial Intelligence and Human Cognition in Cardiovascular Medicine (pp. 157-162). Elsevier.
    DOI
    2022 Mehta, O., Liao, Z., Jenkinson, M., Carneiro, G., & Verjans, J. (2022). Machine Learning in Medical Imaging - Clinical Applications and Challenges in Computer Vision. In Artificial Intelligence in Medicine: Applications, Limitations and Future Directions (pp. 79-99). Springer Nature Singapore.
    DOI Scopus2

  • Conference Papers
    Year Citation
    2023 Guan, Q., Xie, Y., Yang, B., Zhang, J., Liao, Z., Wu, Q., & Xia, Y. (2023). Unpaired Cross-Modal Interaction Learning for COVID-19 Segmentation on Limited CT Images. In H. Greenspan, A. Madabhushi, P. Mousavi, S. Salcudean, J. Duncan, T. Syeda-Mahmood, & R. Taylor (Eds.), Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) Vol. 14222 LNCS (pp. 603-613). CANADA, Vancouver: SPRINGER INTERNATIONAL PUBLISHING AG.
    DOI
    2023 Phan, M. -H., Liao, Z., Verjans, J. W., & To, M. -S. (2023). Structure-Preserving Synthesis: MaskGAN for Unpaired MR-CT Translation.. In H. Greenspan, A. Madabhushi, P. Mousavi, S. Salcudean, J. Duncan, T. F. Syeda-Mahmood, & R. H. Taylor (Eds.), MICCAI (10) Vol. 14229 (pp. 56-65). Springer.
    2021 Shen, H., Liao, K., Liao, Z., Doornberg, J., Qiao, M., Van Den Hengel, A., & Verjans, J. W. (2021). Human-AI interactive and continuous sensemaking: A case study of image classification using scribble attention maps. In Proceedings of the Conference on Human Factors in Computing Systems (CHI'21) (pp. 1-8). New York, NY: Association for Computing Machinery.
    DOI Scopus4 WoS3
    2020 Liao, Z., Liu, L., Wu, Q., Teney, D., Shen, C., Van Den Hengel, A., & Verjans, J. (2020). Medical data inquiry using a question answering model. In Proceedings: 2020 IEEE 17th International Symposium on Biomedical Imaging (ISBI 2020) Vol. 2020-April (pp. 1490-1493). online: IEEE.
    DOI Scopus7 WoS3
    2020 Xie, Y., Zhang, J., Liao, Z., Verjans, J., Shen, C., & Xia, Y. (2020). Pairwise Relation Learning for Semi-supervised Gland Segmentation.. In A. L. Martel, P. Abolmaesumi, D. Stoyanov, D. Mateus, M. A. Zuluaga, S. K. Zhou, . . . L. Joskowicz (Eds.), MICCAI (5) Vol. 12265 (pp. 417-427). Switzerland: Springer Nature.
    DOI Scopus22
    2020 Xie, Y., Zhang, J., Liao, Z., Verjans, J., Shen, C., & Xia, Y. (2020). Pairwise Relation Learning for Semi-supervised Gland Segmentation.. In A. L. Martel, P. Abolmaesumi, D. Stoyanov, D. Mateus, M. A. Zuluaga, S. K. Zhou, . . . L. Joskowicz (Eds.), MICCAI (5) Vol. 12265 (pp. 417-427). Switzerland: Springer Nature.
    DOI
    2020 Liao, Z., Wu, Q., Shen, C., Van Den Hengel, A., & Verjans, J. (2020). AIML at VQA-Med 2020: Knowledge inference via a skeleton-based sentence mapping approach for medical domain visual question answering. In L. Cappellato, C. Eickhoff, N. Ferro, & A. Névéol (Eds.), Proceedings of the 11th International Conference of the CLEF Initiative (CLEF 2020), as published in CEUR Workshop Proceedings Vol. 2696 (pp. 1-14). online: CEUR-WS.
    Scopus6
    2020 Zhang, J., Xie, Y., Liao, Z., Verjans, J., & Xia, Y. (2020). EfficientSeg: A Simple But Efficient Solution to Myocardial Pathology Segmentation Challenge. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) Vol. 12554 LNCS (pp. 17-25). Switzerland: Springer International Publishing.
    DOI Scopus8
    2019 Jafari, M. H., Liao, Z., Girgis, H., Pesteie, M., Rohling, R., Gin, K., . . . Abolmaesumi, P. (2019). Echocardiography Segmentation by Quality Translation Using Anatomically Constrained CycleGAN. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) Vol. 11768 LNCS (pp. 655-663). Switzerland: Springer International Publishing.
    DOI Scopus14
    2019 Behnami, D., Liao, Z., Girgis, H., Luong, C., Rohling, R., Gin, K., . . . Abolmaesumi, P. (2019). Dual-View Joint Estimation of Left Ventricular Ejection Fraction with Uncertainty Modelling in Echocardiograms. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) Vol. 11765 LNCS (pp. 696-704). Switzerland: Springer International Publishing.
    DOI Scopus16
    2019 Liao, Z., Jafari, M. H., Girgis, H., Gin, K., Rohling, R., Abolmaesumi, P., & Tsang, T. (2019). Echocardiography View Classification Using Quality Transfer Star Generative Adversarial Networks. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) Vol. 11765 LNCS (pp. 687-695). Switzerland: Springer International Publishing.
    DOI Scopus9
    2019 Jafari, M. H., Girgis, H., Abdi, A. H., Liao, Z., Pesteie, M., Rohling, R., . . . Abolmaesumi, P. (2019). Semi-supervised learning for cardiac left ventricle segmentation using conditional deep generative models as prior. In Proceedings of the 2019 IEEE 16th International Symposium on Biomedical Imaging (ISBI) Vol. 2019-April (pp. 649-652). online: IEEE.
    DOI Scopus27
    2019 Vaseli, H., Liao, Z., Abdi, A. H., Girgis, H., Behnami, D., Luong, C., . . . Tsang, T. (2019). Designing lightweight deep learning models for echocardiography view classification. In Progress in Biomedical Optics and Imaging - Proceedings of SPIE Medical Imaging 2019 Vol. 10951 (pp. 1-8). online: SPIE.
    DOI Scopus21
    2018 Van Woudenberg, N., Liao, Z., Abdi, A. H., Girgis, H., Luong, C., Vaseli, H., . . . Abolmaesumi, P. (2018). Quantitative echocardiography: Real-time quality estimation and view classification implemented on a mobile android device. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) Vol. 11042 LNCS (pp. 74-81). Switzerland: Springer International Publishing.
    DOI Scopus9
    2018 Jafari, M. H., Girgis, H., Liao, Z., Behnami, D., Abdi, A., Vaseli, H., . . . Abolmaesumi, P. (2018). A unified framework integrating recurrent fully-convolutional networks and optical flow for segmentation of the left ventricle in echocardiography data. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) Vol. 11045 LNCS (pp. 29-37). Switzerland: Springer International Publishing.
    DOI Scopus38
    2016 Liao, Z., & Carneiro, G. (2016). On the importance of normalisation layers in deep learning with piecewise linear activation units. In Proceedings of the 2016 IEEE Winter Conference on Applications of Computer Vision (pp. 1-8). Lake Placid, NY: IEEE.
    DOI Scopus29 WoS1
    2015 Liao, Z., & Carneiro, G. (2015). The use of deep learning features in a hierarchical classifier learned with the minimization of a non-greedy loss function that delays gratification. In Proceedings of the 2015 IEEE International Conference on Image Processing Vol. 2015-December (pp. 4540-4544). Quebec City, CANADA: IEEE.
    DOI Scopus3 WoS3
    2013 Carneiro, G., Liao, Z., & Chin, T. (2013). Closed-loop deep vision. In Proceedings of the 2013 International Conference on Digital Image Computing: Techniques and Applications, DICTA 2013 (pp. 1-8). USA: IEEE.
    DOI

  • Conference Items
    Year Citation
    2022 Dorraki, M., Liao, Z., Abbott, D., Psaltis, P. J., Baker, E., Bidargaddi, N., . . . Verjans, J. W. (2022). Cardiovascular disease risk prediction via machine learning using mental health data. Poster session presented at the meeting of EUROPEAN HEART JOURNAL. OXFORD UNIV PRESS.

  • 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.
    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.
    2023 Zhang, Z., Qi, X., Zhang, B., Wu, B., Le, H., Jeong, B., . . . Hartley, R. (2023). SegReg: Segmenting OARs by Registering MR Images and CT Annotations.

2022

  • Accelerating Drug Discovery with Machine Learning. DIGI + FAME Strategy Internal Grant 2021, University of Adelaide. ($20,000, Co-CI)
  • Faculty of Health and Medical Sciences Research Infrastructure Funding Awards 2022, University of Adelaide. ($25,000, Co-CI)
  • AI lead on the NHMRC partnership Cardiovascular Chest Pain analysis project. Collaboration with Flinders Medical Centre (https://healthtranslationsa.org.au/project/rapid-x-ai/).
  • Orthopedics AI Research Collaboration with Flinders Medical Centre (FMC), Australia and University Medical Centre Groningen (UMCG), The Netherlands. ($290,000 for one postdoc, Co-CI)

2023

  • Chronic myelomonocytic leukaemia AI analysis. A SA Pathology collaboration supported by the state government's funding to AIML. (https://www.sapathology.sa.gov.au/wps/wcm/connect/sa+pathology+internet+content+new/content/news/ai+and+pathology).
  • A predictive model for IVF cycle outcomes from personalised granulosa cell profile. Collaboration with Robinson Research Institute (RRI Innovation Seed Funding, $20,000, Co-CI)
  • Advancing Diagnosis or Treatment of Child and Adolescent Rheumatic Diseases. The Hospital Research Foundation. ($125,000, CI-A)
  • AutoMedic: A scalable, smart solution to detect and resolve medicine harm. MRFF National Critical Research Infrastructure ($2,923,818, Co-CI)

 

Awards:

Winner of the 2020 ImageCLEF VQA-Med and VQG-Med challenge (https://www.aicrowd.com/challenges/imageclef-2020-vqa-med-vqa/leaderboards, https://set.adelaide.edu.au/news/list/2020/06/10/winners-of-the-imageclef-2020-medical-vqa-challenge)

Master Research Project Supervision

  • Master of AIML/CS (6 students, 2024, trimester/semester 1)

 

  • 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
    2024 Co-Supervisor Advancing Medical Image Analysis with Insights from Large-scale Foundation Models Doctor of Philosophy Doctorate Full Time Yunxiang Liu
    2023 Principal Supervisor Explainable and Semantically Meaningful Deep Learning Models for Medical Risk Prediction and Diagnostics Doctor of Philosophy Doctorate Full Time Mr Townim Faisal Chowdhury
    2023 Co-Supervisor Photonics and Machine learning approaches to Detect Environment, Physiology and Disease Doctor of Philosophy Doctorate Full Time Ms Madeleine Cochrane
    2022 Co-Supervisor Computer Vision Doctor of Philosophy Doctorate Full Time Mr Yongtao Ge
    2022 Principal Supervisor Improving the Few-Shot Generalization of Data-to-Text Generation Models Doctor of Philosophy Doctorate Full Time Mr Xuan Ren
    2022 Co-Supervisor Toward efficient 2D human pose estimation with transformer and conditional Convolution Doctor of Philosophy Doctorate Full Time Mr Weian Mao
    2021 Co-Supervisor Towards Accurate Semi-Supervised Semantic Segmentation with Fewer Annotations Doctor of Philosophy Doctorate Full Time Miss Jinchao Ge
    2020 Co-Supervisor Scalable deep learning for scene understanding Doctor of Philosophy Doctorate Full Time Mr James Paul Bockman

  • Past Higher Degree by Research Supervision (University of Adelaide)
    Date Role Research Topic Program Degree Type Student Load Student Name
    2021 - 2024 Co-Supervisor Towards Effective and Efficient Semantic Segmentation Doctor of Philosophy Doctorate Full Time Mr Bowen Zhang
    2020 - 2021 Co-Supervisor Efficient Fully Convolutional Networks for Dense Prediction Tasks Doctor of Philosophy Doctorate Full Time Ms Yifan Liu
    2020 - 2023 Co-Supervisor Label-Efficient Segmentation for Diverse Scenarios Doctor of Philosophy Doctorate Full Time Mr Yunzhi Zhuge
  • Position: Grant-Funded Researcher (C)
  • Phone: 83132070
  • Email: zhibin.liao@adelaide.edu.au
  • Fax: 83134366
  • Campus: North Terrace
  • Building: Australian Institute for Machine Learning, floor 2
  • Org Unit: Australian Institute for Machine Learning - Projects
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