Xianglun Mao
Quantitative Scientist
San Francisco Bay Area United States
Summary
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Senior🎓
Top SchoolXianglun (Vincent) Mao is a quantitative scientist with eight years of experience developing AI-driven, motion-robust cardiac MRI methods and advancing quantitative imaging at the intersection of medical research and product engineering. He has led translation of deep learning techniques into deployable MRI features at GE Healthcare and designed novel reconstruction and fast parametric mapping algorithms during postdoctoral work at Cedars-Sinai. Now at Meta he applies quantitative AI to health and wellness, blending rigorous academic training (PhD, Purdue) with hands-on product impact and close collaborations with Stanford clinical and AI groups. Known for combining signal-processing rigor, constrained optimization for RF/pTx design, and practical deep learning acceleration, he often tackles problems that require both pulse-sequence engineering and scalable model deployment.
8 years of coding experience
13 years of employment as a software developer
Bachelor of Engineering (B.E.), Computer Science, Bachelor of Engineering (B.E.), Computer Science at Beijing University of Post and TelecommunicationsDoctor of Philosophy (PhD), Electrical and Computer Engineering, Doctor of Philosophy (PhD), Electrical and Computer Engineering at Purdue UniversityGithub contributions (2)
VincentMao/MR_VOP_kMeans
Feb 2020 - May 2020
Contributions:4 commits, 14 pushes, 4 branches in 3 months
VincentMao/ME-EPI-VF
Sep 2017 - Sep 2017
Contributions:1 push, 1 branch in 1 day
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