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Zongyuan Ge

Dr

Accepting PhD Students

20142020
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Personal profile

Biography

ZongYuan Ge, is currently a Senior Research Fellow and Adjunct Senior Lecturer at Monash Faculty of Engineering and also serve as a Deep Learning Specialist at NVIDIA AI Technology Centre. 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 Ph.D. 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)
  • 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

Zongyuan’s dermatology work is a joint collaboration between industry company Molemap Ltd and research institute. This work has been awarded for IBM Scientific Research Accomplishment Award and IBM Manager Choice Award. These findings have pushed forward the AI implementation in the field of skin cancer screening service and generated over one million revenue from the product. This research led to 4 technical PIC conference papers (2 as lead-author), an abstract presented in Dermatology World Congress 2017, one clinical journal (under preparation for submission to JAMA Dermatology) and 2 patent filed.    
 
Zongyuan’s recent AI work on ophthalmology has lead a team of 12 research engineers and built a fundus based eye disease screening system. The system is able to provide diagnosis suggestion over more than 36 fundus diseases including diabetic retinopathy (DR), age-related macular degeneration and glaucoma. This system is trained over 5 million images labelled by over 100 ophthalmologists for 3 years. In 2018, this system has provided eye care service for more than 8 million people in major health checking institutes and major hospitals. 

Keywords

  • Deep Learning
  • Medical Imaging
  • Artificial Intelligence
  • Computer Vision
  • Robotics

Network Recent external collaboration on country level. Dive into details by clicking on the dots.

Projects 2019 2020

Cardiorespiratory function as a non-invasive biomarker for detecting seizures with artificial intelligence: Utilising data from long-term patient recordings from an epilepsy monitoring unit

O'Brien, T., Kwan, P., Sivathamboo, S., Perucca, P., Ge, Z., Le, T., Phung, D., Bonnington, P. & Piccenna, L.

8/04/19 → 8/04/20

Project: Research

AMA: Airdoc medical AI projects donation

Ge, Z., Bonnington, P. & Drummond, T.

AirDoc LLC

1/04/19 → 1/04/19

Project: Research

Research Output 2014 2018

Deep multiscale convolutional feature learning for weakly supervised localization of chest pathologies in X-ray images

Sedai, S., Mahapatra, D., Ge, Z., Chakravorty, R. & Garnavi, R., 1 Jan 2018, Machine Learning in Medical Imaging: 9th International Workshop, MLMI 2018, Held in Conjunction with MICCAI 2018, Granada, Spain, September 16, 2018, Proceedings. Shi, Y., Suk, H-I. & Liu, M. (eds.). Cham Switzerland: Springer, Vol. 11046. p. 267-275 9 p. (Lecture Notes in Computer Science; vol. 11046).

Research output: Chapter in Book/Report/Conference proceeding › Conference Paper › Research › peer-review

Editorial: Artificial Intelligence for Mobile Robotic Networks

Lu, H., He, L., Zhou, Q. & Ge, Z., 1 Apr 2018, In : Mobile Networks and Applications. 23, 2, p. 326-327 2 p.

Research output: Contribution to journal › Editorial › Other › peer-review

Open Access
File

FDCNet: filtering deep convolutional network for marine organism classification

Lu, H., Li, Y., Uemura, T., Ge, Z., Xu, X., He, L., Serikawa, S. & Kim, H., 1 Sep 2018, In : Multimedia Tools and Applications. 77, 17, p. 21847-21860 14 p.

Research output: Contribution to journal › Article › Research › peer-review

Joint registration and segmentation of xray images using generative adversarial networks

Mahapatra, D., Ge, Z., Sedai, S. & Chakravorty, R., 1 Jan 2018, Machine Learning in Medical Imaging: 9th International Workshop, MLMI 2018, Held in Conjunction with MICCAI 2018, Granada, Spain, September 16, 2018, Proceedings. Shi, Y., Suk, H-I. & Liu, M. (eds.). Cham Switzerland: Springer, Vol. 11046. p. 73-80 8 p. (Lecture Notes in Computer Science ; vol. 11046).

Research output: Chapter in Book/Report/Conference proceeding › Conference Paper › Research › peer-review

Learning Context Flexible Attention Model for Long-Term Visual Place Recognition

Chen, Z., Liu, L., Sa, I., Ge, Z. & Chli, M., 1 Oct 2018, In : IEEE Robotics and Automation Letters. 3, 4, p. 4015-4022 8 p., 8421024.

Research output: Contribution to journal › Article › Research › peer-review