XiaoWu
Summary
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RockstarXiao Wu is a quantitative researcher and biostatistician based in New York with seven years of experience at the intersection of health AI, causal inference, and Bayesian/nonparametric methods. Currently an Assistant Professor at Columbia and a Quantitative Scientist on Meta's Health AI team, Xiao blends academic rigor—PhD training and postdocs at Harvard and Stanford—with industry-facing evaluation and benchmark curation for large language models in healthcare. A Forbes 30 Under 30 honoree, Xiao has a track record of translating complex statistical theory into practical tools for spatio-temporal and clinical research and has contributed to methodological advances in adaptive Bayesian designs and network-interference experimentation. Fluent in both quantitative research and applied product evaluation, Xiao’s work uniquely bridges rigorous causal methods and real-world health AI assessment, and their bilingual outlook (Chinese-English) and multidisciplinary training in law and math hint at a rare combination of technical depth and broader regulatory and ethical awareness.
7 years of coding experience
Github Skills (3)
pytorch9
python4
computer-vision4
Programming languages (3)
Github contributions (5)
2209520576/Image-Processing-Algorithm
Feb 2019 - Nov 2019
基于OPenCV实现图像处理各种常用算法
Contributions:58 commits, 59 pushes, 1 branch in 8 months
2209520576/CV-Image-Processing
Mar 2020 - Jun 2020
Datawhale 第12期组队学习 -计算机视觉基础（图像处理）
Contributions:138 commits, 5 PRs, 146 pushes in 2 months
pythoncomputer-vision
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