Projects per year
Personal profile
Biography
ZongYuan Ge, is currently an Associate Professor at Monash University and also serve as a Deep Learning Specialist at NVIDIA AI Technology Centre. He is also the head of Monash Medical AI Group (www.mmai.group).
Before he joined Monash Zongyuan was a research scientist at IBM Research Australia doing research in medical AI during 2016-2018.
He has been awarded science accomplishment award and manager choice of the year inside IBM for his excellent contributions to those projects. In 2017, Zongyuan was selected as one of the 200 Most Qualified Young Researchers in Computer and Mathematics by the Scientific Committee of the Heidelberg Laureate Forum Foundation in 2017.
He has a strong background in statistical analysis, machine learning and computer vision research. So far, he has published more than 30 peer-reviewed publications and patents. He has led and contributed to six international projects in the areas of dermatology, ophthalmology and radiology with major industry companies like IBM Watson Health, medical AI unicorn startup Airdoc and medical service provider Molemap. These findings have been translated into health products and services that foster effective infectious diseases interventions in Asia-Pacific.
Formerly Zongyuan was a PhD candidate with Australian Centre for Robotics Vision at the Queensland University of Tech and worked with Prof. Peter Corke, Dr Chris McCool and Dr Conrad Sanderson. He has enthusiasm for AI, computer vision, medical image, robotics and deep learning research.
Two PhD scholarships are available in Zongyuan's medical AI team in 2019, please contact him if you are interested in computer vision, machine learning or medical AI.
Community service
Professional Memberships and Service
- 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
Consulting
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
- Robotics
Network
-
Machine learning models for personalised epilepsy management
Kwan, P., Chen, B., Zhang, D., Foster, E., Haffari, R., Vaughan, D., Lawn, N. D., Perucca, P., Nicolo, J., Carney, P., Brodie, M. J., Ge, Z. & Anderson, A.
1/01/22 → 31/12/24
Project: Research
-
AI for estimating global bushfire smoke and its health burden
Guo, Y., Ge, Z., Li, S. & Song, J.
1/09/21 → 31/08/22
Project: Research
-
Stakeholder perspectives on Machine learning clinical decision support in epilepsy
Kwan, P., Sparrow, R., Reeder, S., Ge, Z., Foster, E. & Howard, M.
23/08/21 → 23/12/22
Project: Research
-
Reconceiving early detection of melanoma
Mar, V., Janda, M., Soyer, P., Fernandez-Peñas, P., Cust, A. E., Morton, R., Wolfe, R., Scolyer, R. A., Ge, Z. & Lawn, C.
1/07/21 → 30/06/26
Project: Research
File -
Transforming the paradigm of epilepsy care with precision medicine
Wolvetang, E. J., Kwan, P., Vadlamudi, L., O'Brien, T., Ge, Z., Anderson, A., Shaker, M., Antonic-Baker, A., Leeson, H. & Rollo, B.
Department of Health (Australia)
1/06/21 → 31/05/24
Project: Research
-
ASPIRER: A new computational approach for identifying non-classical secreted proteins based on deep learning
Wang, X., Li, F., Xu, J., Rong, J., Webb, G. I., Ge, Z., Li, J. & Song, J., Mar 2022, In: Briefings in Bioinformatics. 23, 2, p. 1-12 12 p., bbac031.Research output: Contribution to journal › Article › Research › peer-review
-
Auto-FSL: searching the attribute consistent network for few-shot learning
Zhang, L., Wang, S., Chang, X., Liu, J., Ge, Z. & Zheng, Q., Mar 2022, In: IEEE Transactions on Circuits and Systems for Video Technology. 32, 3, p. 1213-1223 11 p.Research output: Contribution to journal › Article › Research › peer-review
-
Autonomous incident detection on spectrometers using deep convolutional models
Zhang, X., Zhang, D., Leye, A., Scott, A., Visser, L., Ge, Z. & Bonnington, P., 2022, In: Sensors. 22, 1, 18 p., 160.Research output: Contribution to journal › Article › Research › peer-review
Open AccessFile -
Contextual ensemble network for semantic segmentation
Zhou, Q., Wu, X., Zhang, S., Kang, B., Ge, Z. & Jan Latecki, L., Feb 2022, In: Pattern Recognition. 122, 11 p., 108290.Research output: Contribution to journal › Article › Research › peer-review
5 Citations (Scopus) -
Application of Comprehensive Artificial intelligence Retinal Expert (CARE) system: a national real-world evidence study
Lin, D., Xiong, J., Liu, C., Zhao, L., Li, Z., Yu, S., Wu, X., Ge, Z., Hu, X., Wang, B., Fu, M., Zhao, X., Wang, X., Zhu, Y., Chen, C., Li, T., Li, Y., Wei, W., Zhao, M., Li, J. & 16 others, , Aug 2021, In: The Lancet Digital Health. 3, 8, p. e486-e495 10 p.Research output: Contribution to journal › Article › Research › peer-review
Open Access6 Citations (Scopus)