Kaiwen Wu

Graduate Student Researcher

California, United States
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Summary

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Kaiwen Wu is a graduate student researcher in California specializing in theoretical deep learning and its intersections with cognitive processes, with eight years of research experience spanning adversarial example analysis, class-agnostic feature extraction, and predictive coding models. Based at UC San Diego and collaborating with the San Diego Supercomputer Center, Kaiwen profiles applications and generates labeled datasets to support deep-learning performance prediction. His work blends rigorous MS-level study in Artificial Intelligence with hands-on lab experiments on layerwise vulnerability of networks and biologically inspired binocular predictive coding. Preparing for PhD study, he brings a strong engineering foundation from a high-achieving undergraduate degree in Internet of Things and a knack for connecting theoretical insights to practical profiling and labeling pipelines.
code8 years of coding experience
bookUniversity of California, San Diego
bookBachelar of Engineering, The Internet of Things Engineering, Accumulative GPA 91.72/100, Bachelar of Engineering, The Internet of Things Engineering, Accumulative GPA 91.72/100 at Beijing University of Posts and Telecommunications
bookUniversitat Politècnica de València
languagesEnglish, Chinese
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Github Skills (29)

pytorch10
gaussian-processes10
bayesian10
gpu-acceleration10
simulation9
python8
gpytorch8
gpu8
machine-learning8
image-synthesis8
adversarial-attacks7
numpy7
deep-learning7
botorch6
neural-network6

Programming languages (3)

HTMLJupyter NotebookPython

Github contributions (5)

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kayween/kayween.github.io

May 2024 - Dec 2025

Contributions:5 PRs, 66 pushes, 17 branches in 1 year 7 months
Contributions:5 commits, 10 pushes, 1 branch in 1 year 3 months
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