Peng Li
TD Sr. Process Integration Manager And Next Gen 3D NAND NTI Lead
Liaoning, China
Summary
🤩
Rockstar🎓
Top SchoolPeng Li is a senior process integration leader with 26 years of semiconductor experience, currently driving next-generation 3D NAND NTI and process integration at Intel. He combines deep device and physics expertise (Ph.D. in Physics/Nanoscience) with hands-on HVM tool sustaining and fab startup experience, having led multiple product transfers and the development of Intel’s 5th‑gen 192‑layer QLC NAND. Known for translating research into production, he has published in top journals and led projects that delivered yield, cost and throughput gains across fabs. Unusually for a process integration manager, he also contributes to open-source performance optimization in computer vision (notably OpenCV OpenCL kernels), reflecting a rare blend of device physics, high-volume manufacturing discipline, and software performance engineering.
26 years of coding experience
11 years of employment as a software developer
Ph.D., Physics/Nanoscience, Ph.D., Physics/Nanoscience at Duke UniversityM.S., Physics, M.S., Physics at Tsinghua University
Chinese, English
Github Skills (9)
opencl10
computer-vision10
c-language10
cprogramming-language10
performance-optimization10
image-processing10
neural-network9
convolutional-neural-networks9
deep-learning8
Programming languages (3)
Github contributions (5)
opencv/opencv
Oct 2016 - Jul 2018
Open Source Computer Vision Library
Role in this project:
Back-end Developer & Performance Engineer
Back-end Developer & Performance EngineerContributions:64 commits in 1 year 9 months
Contributions summary:Peng contributed to the performance optimization of OpenCL kernels within the OpenCV library, specifically focusing on computer vision algorithms. Their work involved rewriting and optimizing existing kernels for functions like box filtering, morphological operations (erode/dilate), Gaussian blur, Sobel/Scharr, Laplacian and other image processing algorithms to improve execution speed. They introduced optimized kernels for specific image formats and kernel sizes, leading to significant performance gains.
pythonvisiondeep-learningc-plus-pluscomputer-vision
pli2-intel/github_actions_demo
May 2021 - Jun 2021
Contributions:27 PRs, 23 pushes, 26 branches in 21 days
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