Associate Professor Zongyuan Ge conducts interdisciplinary research at the boundary between artificial intelligence, computer-aided diagnosis, biomedical engineering, medical imaging and machine learning and is 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 and prognosis for eye (ophthalmology), skin (dermatology), heart (cardiovascular) and neurodegeneration diseases. He is also one of Australia’s most in-demand experts in technologies 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 and the Chief Research Officer at Ascertain. 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”.
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.
