Rui Shen is a bioengineering PhD turned Associate at McKinsey & Company with nine years of experience at the intersection of medical image analysis, deep learning, and network neuroscience. At UPenn’s DiCIPHR lab he developed connectomic biomarkers and graph-based deep learning methods to parse heterogeneity in developmental disorders, graduating with a 4.0 GPA. He previously honed computer vision and medical image processing skills at Johns Hopkins and industry internships (SenseTime, Philips), combining strong algorithmic foundations with translational research rigor. Rui is adept at improving model generalizability for clinically relevant neuroimaging tasks and brings hands-on experience in teaching and mentorship across biostatistics, compressive sensing, and ML. Outside work he balances analytical curiosity with creativity—mixology, dance, and hiking—and is transitioning academic insights into strategy and product-focused impact at McKinsey.
9 years of coding experience
8 years of employment as a software developer
Johns Hopkins University
Bachelor of Science in Engineering (B.S.E), 89.13/100, Bachelor of Science in Engineering (B.S.E), 89.13/100 at Southeast University
Doctor of Philosophy - PhD, Bioengineering and Biomedical Engineering, 4.0/4.0, Doctor of Philosophy - PhD, Bioengineering and Biomedical Engineering, 4.0/4.0 at University of Pennsylvania
Contributions:17 commits, 10 PRs, 10 pushes in 1 month
hl7deep-learningmachine-learningdl-coursegraph
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