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Personal profile


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


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.    
Zongyuans 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. 

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):

  • SDG 3 - Good Health and Well-being

Research area keywords

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


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