Yizhou Wang
Pittsburgh, Pennsylvania, United States
Summary
👤
Senior🎓
Top SchoolYizhou Wang is a Machine Learning Engineer with a decade of software and research experience, blending a strong mathematics background with hands-on development in React, Node, and C++. He has implemented applied ML solutions—from TDA-driven protein state classification that reduced reliance on costly crystallography to LLM-guided reward evaluation pipelines for video-informed reinforcement learning in autonomous driving. Comfortable across R and Python for data analysis and with research interests in statistical learning theory and variational inference, he moves fluidly between prototype research and production-focused systems. Based in Pittsburgh and trained at Carnegie Mellon, Yizhou is especially effective at translating mathematical insight into practical pipelines that cut cost and accelerate model validation.
10 years of coding experience
Bachelor of Science - BS, Computer Science, Bachelor of Science - BS, Computer Science at Carnegie Mellon University
Chinese, English, French
Github Skills (15)
autoencoder9
variational-autoencoder9
language-model8
pytorch8
reinforcement-learning8
density-estimation7
variational-inference7
python4
hpc-applications3
machine-learning3
agentic2
ai-agent2
sequence-to-sequence1
hpc1
scientific-computing1
Programming languages (2)
Github contributions (5)
kingofspace0wzz/wae-rnf-lm
Apr 2019 - Apr 2020
Pytorch Implemetation for our NAACL2019 Paper "Riemannian Normalizing Flow on Variational Wasserstein Autoencoder for Text Modeling" https://arxiv.org/abs/1904.02399
Contributions:7 commits, 2 PRs, 4 pushes in 11 months
autoencoderpytorchvariational-autoencodervariational-inferencelanguage-model
kingofspace0wzz/paper
Mar 2019 - Mar 2020
Contributions:47 commits, 18 pushes in 1 year
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