Shern Tan is an AI Model Ops Engineer with 13 years of software and research experience, currently focused on productionizing ML models at UBS after recent roles building medical imaging platforms. He has a PhD in Computer Science and a track record of architecting scalable backend and microservice systems for retina image analysis—designing GraphQL APIs, ML pipelines and distributed task queues that powered clinical-grade workflows. Previously as CTO and Lead Engineer he built high-throughput message-oriented middleware handling hundreds to thousands of messages per second, and he holds practical certifications including a Self-Driving Car Nanodegree and AWS/data neural network training. Shern combines deep academic work in cross-modal image sonification with hands-on deployment experience, contributing patents and publications in image processing while focusing on real-world impact in ophthalmology. Based in Basel, he brings both research rigor and production-first engineering to bridge models from lab prototypes into reliable medical services.
13 years of coding experience
12 years of employment as a software developer
Bachelor of Technology (BTech) Information Communication Technology, Bachelor of Technology (BTech) Information Communication Technology at Universiti Teknologi PETRONAS
Doctor of Philosophy - PhD Computer Science, Doctor of Philosophy - PhD Computer Science at University of Nottingham Malaysia
Self-Driving Car Nanodegree Computer Science, Self-Driving Car Nanodegree Computer Science at Udacity
Contributions:136 commits, 27 PRs, 112 pushes in 1 year
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