Tengda Han is a research scientist specializing in computer vision with a decade of experience bridging academia and industry, currently working at Google DeepMind after a postdoc at the Visual Geometry Group, University of Oxford. His work spans deep learning for visual intelligence, informed by hands-on contributions to projects like Flamingo during a DeepMind internship and long-term research at VGG. Tengda combines rigorous PhD-level research with applied ML engineering experience from internships at Seeing Machines and open-source contributions dating back to Google Summer of Code. He brings strength in turning complex visual AI problems into reproducible research and prototype systems that influence both publications and product-facing models. Based in Oxford, he pairs international education—ANU engineering honors and business studies in China—with a track record of collaborating across large research labs and industry teams. Colleagues describe him as equally comfortable writing core model code, shepherding experiments, and communicating insights to multidisciplinary stakeholders.
10 years of coding experience
1 year of employment as a software developer
Australian National University
Doctor of Philosophy - PhD, Computer Vision, Doctor of Philosophy - PhD, Computer Vision at University of Oxford
Bachelor of Business Administration (B.B.A.), Business Administration and Management, General, Bachelor of Business Administration (B.B.A.), Business Administration and Management, General at Renmin University of China
Contributions:38 commits, 36 pushes, 1 branch in 2 months
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