Projects per year
Associate Professor Zongyuan Ge conducts interdisciplinary research at the boundary between Medical Artificial Intelligence, Computer-aided Diagnosis, Biomedical Engineering, Digital Health, Medical Imaging and Machine Learning and is a multi-award-winning medical information science and technology entrepreneur. His research leverages cutting-edge AI technologies using large-scale multi-modality medical data including imaging, medical records, gene data and models the clinicians’ medical knowledge underlying tasks like diagnosis, prognosis, and treatment for eye (ophthalmology), skin (dermatology), heart (cardiovascular) and neurodegeneration diseases such as epilepsy and multiple sclerosis. He is also one of Australia’s most in-demand experts in technology, including medical robotics and artificial intelligence, and is a passionate science communicator.
He currently holds the tenure position of Associate Professor at the Monash University, the Faculty of IT and the Faculty of Engineering. He also holds NVIDIA AI Fellowship and serves as the Chief Scientist at Monash-Airdoc Research Centre. He is the Founding Director of the Monash Medical AI group (https://www.monash.edu/mmai-group) with over fully funded 25+ PhD students (internal + external), and 5 Research Fellows.
His research has helped attract more than 25+ million dollars in funding as either primary chief investigator or leading chief investigator from grant bodies, including the National Health and Medical Research Council (NHMRC), Medical Research Future Fund (MRFF), The Australian Research Data Commons (ARDC), CSIRO, The Australian Research Council (ARC) and industry funding from NVIDIA, The Agilent Thought Leader Program, Molemap/Kahu, Ascertain, Shukun and Airdoc.
His h-index is 30, with 5500+ citations only five years post PhD. Zongyuan has strong publication record of 100+ first or senior author top-tier (ERA ranking A*/A) journals and technical conferences in the machine learning and medical AI field. His research papers have been published in top-tier journals and conferences such as The Lancet Digital Health (IF=36.615), The British Medical Journal (IF=96.22), JAMA Neurology (IF=29.91), Nature Nanotechnology (IF=39.21), Brief in Bioinformatics (IF=11.62), Hypertension (IF=10.19), IEEE Transactions on Pattern Analysis and Machine Intelligence (IF=24.31), IEEE Transactions on Medical Imaging (TMI) (IF=10.048), Medical Imaging Analysis (IF=13.83) and top-tier conference including NeurIPS, ICLR, CVPR, ICCV, ECCV, KDD, AAAI, IJCAI and MICCAI.
His work has been recognised by many international and national awards, including the 200 Most Qualified Young Researchers in Computer and Mathematics by the Scientific Committee of the Heidelberg Laureate Foundation, IBM Scientific Research Accomplishment Award, IBM Manager Choice Award, NVIDIA AI Fellowship, the Agilent Thought Leader Program, the Australian Pattern Recognition Society (APRS) Early Career Researcher Award in 2021 and Monash Exceptional Achievement Award. The products developed by Airdoc and his team have also won honours such as “the highest award of artificial intelligence in China”–Wu Wenjun Award for Artificial Intelligence Science and Technology twice in 2019, 2022 and “the case of Microsoft global AI cooperation in 2018 World Artificial Intelligence Conference”.
As a lifelong medical technology entrepreneur, he has led and contributed to several international research projects in the areas of dermatology, ophthalmology, radiology, and neurology with major industry companies like IBM Watson Health, medical technology unicorn company Airdoc/Eyetelligence and medical/healthcare services providers such as Molemap Clinic, The Alfred Health, Royal Melbourne Hospital, and Princess Alexandra Hospital. A/Prof Ge is also the Chief Scientist for the Airdoc Research Centre (https://www.airdoc.com/) to lead the AI technology and product development team. In 2019, he helped build the Monash-Airdoc Research Centre (with 3.5m total investment) to help developed CFDA, NDPR, CLASS III approved healthcare monitoring products. This eye disease diagnosis AI product has served millions of people in China, India, Japan, South Africa and Australia. According to the financial report, the revenue generated from the ophthalmology AI products A/Prof Ge’s team co-developed has generated 25 million dollars in revenue for the company. Airdoc has been successfully listed on Hongkong Stock Exchange (2251-HK) with a market cap of over 1 billion US dollars (2021, Dec).
A/Prof Ge is actively engaged in the scientific community. He coordinates the NVIDIA Student Ambassador Program as the certified NVIDIA Deep Learning Institute (DLI) instructor in Victoria Australia and runs the Monash-NVIDIA joint centre daily activities, and assists NVIDIA in building a strong AI ecosystem in Australia by delivering one-day AI courses, organising deep learning workshops and giving keynotes, plenaries to general science communities. He is on the program/technical committee of several top-tier conferences, such as AAAI and IJCAI, and associate editor/reviewer for journals such as Scientific report, IEEE Transactions on Medical Imaging and IEEE Transactions on Pattern Analysis and Machine Intelligence. As part of the steering group at the Monash Data Science and AI platform, Zongyuan’s industry expertise developed at IBM and NVIDIA has helped his collaborators to define the prototype of the machine learning algorithm for the healthcare data platform HELIX (https://www.monash.edu/researchinfrastructure/helix/home). His role with Monash eResearch centre and data science & AI platform provides Monash researchers and their collaborators with the ability to access several High-Performance Computing facilities and data science services. This includes the Monash-hosted national specialised data-processing facility for medical imaging and visualisation.
Professional Memberships and Service
- University Ambassador & Certified Instructor for NVIDIA DLI Global Program
- The Australian Research Data Commons (ARDC) Scientific Advisory Committee
- Steering Group member, Monash Data Science and AI platform
- Research Advisory Committee, Australian Centre of Excellence Melanoma Imaging Diagnosis (ACEMID)
- Member at Large, Australian Pattern Recognition Society (APRS)
- Panel Assessors, Monash University Central Clinical School, Faculty of Medicine
- ISAIR Board of Directors, Oceania Vice-Chair
- Cognitive Robotics, Editorial Board Member
- Scientific Reports, Associate Editor
- Artificial intelligence for mobile robotic networks, Editorial Board Member
- Sensors SI, Guest Editor
- ICPR, Industry Committee
- MRFF AI Workshop Coordinator
- ACCV 2022, Organising Committee, Web Chair
- DICTA 2020 (Australasian B), General Chair
- AAAI 2019-2022 (CORE A*) Technical Committee
- IJCAI 2019-2021 (CORE A*) Technical Committee
- ISAIR 2017-2022, General Chair, Program Co-Chair, Area Chair
- ROSNET 2020 program committee
- International Conference on Database Systems 2019, Advanced Applications Tutorial Organiser
- Transactions on Medical Imaging (TMI)
- Computer Vision and Pattern Recognition (CVPR)
- Medical Imaging Computing and Computer-Assisted Intervention (MICCAI)
- IEEE International Conference on Robotics and Automation (ICRA)
- International Joint Conference on Artificial Intelligence (IJCAI)
- IEEE Winter Conference on Applications of Computer Vision (WACV)
- IEEE International Symposium on Biomedical Imaging (ISBI)
- International Conference on Digital Image Computing: Techniques and Applications (DICTA)
- IEEE Transactions on Image Processing (TIP)
- IEEE Transaction on Multimedia (ToM)
- ELSEVIER Computers & Electrical Engineering
- International Journal of Applied Mathematics and Computer Science (AMCS)
- IBM Journal of Research and Development
- Journal of Biomedical and Health Informatics
Expertise related to UN Sustainable Development Goals
In 2015, UN member states agreed to 17 global Sustainable Development Goals (SDGs) to end poverty, protect the planet and ensure prosperity for all. This person’s work contributes towards the following SDG(s):
Research area keywords
- Deep Learning
- Medical Imaging
- Artificial Intelligence
- Computer Vision
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1/02/23 → 31/01/26
PERSONAL: Personalised Selection of Medication for Newly Diagnosed Adult Epilepsy – the PERSONAL Trial
Kwan, P., Chen, B., Lannin, N., Ademi Delaney, Z., Ge, Z., Reutens, D., O'Brien, T., D'Souza, W. J., Perucca, P., Reeder, S., Nikpour, A., Wong, C., Kiley, M., Saw, J., Nicolo, J., Seneviratne, U., Carney, P., Jones, D., Somerville, E. R. & Stapleton, C.
1/02/23 → 31/01/27
CSIRO Data61 Next Generation Graduates Programs: Privacy-Preserving Machine Learning: Technology Development and Adoption
Yuan, X., Liu, J., Ge, Z., Haffari, R., Yang, R., Yi, X., Sakzad, A., Fang, Y., Cui, S., Baiao Dowsley, R., Du, X., Salehi, M., Han, F., Wakefield, R., Abuadbba, S., Wu, T. & Liu, X.
1/01/23 → 31/12/27
AI for assessment of global mortality risk associated with tropical cyclones
Li, S., Guo, Y., Zhao, Q., Vogt, T. & Ge, Z.
1/07/22 → 30/06/24
Skin Imaging and Precision Diagnosis
Janda, M., Soyer, H. P., Mar, V., Fernandez-Peñas, P., Morton, R., Cust, A. E., Wolfe, R., Scolyer, R. A., Caffery, L. & Ge, Z.
7/01/22 → 7/01/25
EEG datasets for seizure detection and prediction— A reviewWong, S., Simmons, A., Rivera-Villicana, J., Barnett, S., Sivathamboo, S., Perucca, P., Ge, Z., Kwan, P., Kuhlmann, L., Vasa, R., Mouzakis, K. & O'Brien, T. J., 2023, (Accepted/In press) In: Epilepsia Open. 16 p.
Research output: Contribution to journal › Review Article › Research › peer-reviewOpen Access
3D matting: a benchmark study on soft segmentation method for pulmonary nodules applied in computed tomographyWang, L., Ye, X., Zhang, D., He, W., Ju, L., Luo, Y., Luo, H., Wang, X., Feng, W., Song, K., Zhao, X. & Ge, Z., Nov 2022, In: Computers in Biology and Medicine. 150, 12 p., 106153.
Research output: Contribution to journal › Article › Research › peer-review
A deep learning system for fully automated retinal vessel measurement in high throughput image analysisShi, D., Lin, Z., Wang, W., Tan, Z., Shang, X., Zhang, X., Meng, W., Ge, Z. & He, M., 22 Mar 2022, In: Frontiers in Cardiovascular Medicine. 9, 12 p., 823436.
Research output: Contribution to journal › Article › Research › peer-reviewOpen Access
A label uncertainty-guided multi-stream model for disease screeningLiu, C., Ge, Z., He, M. & Han, X., 2022, Proceedings of the 2022 IEEE 19th International Symposium on Biomedical Imaging (ISBI). 1st ed. USA: IEEE Computer Society, 5 p. (Proceedings - International Symposium on Biomedical Imaging; vol. 2022-March).
Research output: Chapter in Book/Report/Conference proceeding › Conference Paper › Research › peer-review
A Machine-Learning-Based Risk-Prediction Tool for HIV and Sexually Transmitted Infections Acquisition over the Next 12 MonthsXu, X., Ge, Z., Chow, E. P. F., Yu, Z., Lee, D., Wu, J., Ong, J. J., Fairley, C. K. & Zhang, L., 1 Apr 2022, In: Journal of Clinical Medicine. 11, 7, 14 p., 1818.
Research output: Contribution to journal › Article › Research › peer-reviewOpen Access