Shenjun Zhong is a research fellow and founder with 12 years’ experience applying deep learning to biomedical imaging and production AI systems. Based at Monash and the National Imaging Facility, he builds large-scale medical imaging workflows, drives cross-site federated learning initiatives, and integrates sequence and generative models (LSTM, Transformers) into MRI reconstruction and diffusion imaging pipelines. He also brings industry-grade ML product experience from Telstra, where he developed multi-turn NLP/chatbot systems and optimized serving architectures on cloud. As CTO of a real-time streaming startup, he applies reinforcement learning and time-series prediction in low-latency systems, bridging research and deployable engineering. His background spans mechanical engineering through a PhD in neuroimaging, giving him a rare combo of hardware-aware thinking and cutting-edge data-science expertise.
12 years of coding experience
3 years of employment as a software developer
Bachelor's degree, Mechanical Engineering, Bachelor's degree, Mechanical Engineering at University of Shanghai for Science and Technology
Master's degree, Information Technology (Honors), H1, Master's degree, Information Technology (Honors), H1 at Monash University
Brain imAgiNg Analysis iN Arcana (Banana): brain imaging analysis workflows implemented in the Arcana framework
Contributions:6 PRs, 11 pushes, 2 branches in 2 months
brainarcanaanalysis-workflowsimagingworkflows
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