Wang Chen-hua
Yield Development Engineer at Intel Corporation
Chandler, Arizona, United States
Summary
🤩
Rockstar🎓
Top SchoolWang Chen-hua is a Yield Development Engineer with six years’ experience specializing in semiconductor fabrication, IC packaging yield and reliability, and thermal solutions for high-volume AI client products. At Intel he helped take the Lunar Lake AI client from assembly development to mass production and standardized analysis flows to down-select materials across client and GPU products. Trained as a chemical and biomolecular engineer at Cornell, he combines hands-on process skills (deposition, lithography, etch, ion implantation) with strong data analysis (DOE, JMP, ANOVA), material/chemical characterization, and computational optimization using Python, Pyomo and GAMS. He contributes to high-profile open-source work on OpenVINO—optimizing CPU kernels and adding f16/bf16 support—which reflects his ability to bridge device-level process development with performance-minded software engineering. Based in Chandler, AZ, he also brings cross-disciplinary experience from battery and environmental research, where he translated lab-scale findings into improved cycle life and scalable recycling optimizations.
6 years of coding experience
3 years of employment as a software developer
Bachelor of Engineering - BE, Environmental Engineering, GPA 3.8/4.0, Bachelor of Engineering - BE, Environmental Engineering, GPA 3.8/4.0 at National Cheng Kung UniversityMaster's degree, Chemical and Biomolecular Engineering, Master's degree, Chemical and Biomolecular Engineering at Cornell University Graduate School
Github Skills (8)
computer-vision10
c-language10
deep-learning10
inference10
cprogramming-language10
performance-optimization10
back-end-development10
openvino10
Programming languages (1)
Github contributions (5)
openvinotoolkit/openvino
Jul 2020 - Nov 2022
OpenVINO™ is an open source toolkit for optimizing and deploying AI inference
Role in this project:
Back-end Developer & ML Engineer
Back-end Developer & ML EngineerContributions:1024 reviews, 38 commits, 133 PRs in 2 years 4 months
Contributions summary:Wang contributed to the development of CPU-specific kernels for the OpenVINO toolkit, with a focus on accelerating AI inference. The commits show the implementation of ScatterUpdate-related operations, including support for ScatterUpdate, ScatterElementsUpdate, and ScatterNDUpdate. The user also implemented and optimized interpolation and deconvolution operations, including the integration of f16/bf16 precision support, improving the efficiency of the toolkit. The user further refined the code with optimizations and security fixes.
aiinferenceopenvinodeep-learningcomputer-vision
chenhu-wang/openvino
Jun 2020 - Jul 2026
OpenVINO™ Toolkit - Deep Learning Deployment Toolkit repository
Contributions:5 PRs, 1208 pushes, 149 branches in 6 years 2 months
pytorchcaffe2deep-learningdeploymentopenvino-toolkit
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