Yintong Lu
Machine Learning Engineer at Intel Corporation
Pittsburgh, Pennsylvania, United States
Summary
🤩
Rockstar🎓
Top SchoolYintong Lu is a machine learning engineer with three years of industry and research experience applying deep learning to biomedical, e-commerce, and NLP problems. Currently at Intel and previously building transformer-based NLG and NLU systems at Baidu, she bridges production ML engineering with academic rigor from a Carnegie Mellon MS in Mechanical Engineering and a UC Berkeley BS in Applied Mathematics. Her research work includes generative models for 3D mask contour reconstruction (VAE+GAN) and production-ready feature pipelines for personalized medical devices, reflecting strength in both model innovation and engineering for real-world deployment. Comfortable across Python, PyTorch/Keras, MATLAB, C++ and CAD/FEA tools, she pairs data-driven modeling with hands-on 3D scanning and mesh generation for printable medical solutions. Based in Pittsburgh, she brings a rare combination of biomechanics insight and large-scale ML experience that helps move customized healthcare designs from scan to manufacturable product.
3 years of coding experience
4 years of employment as a software developer
Bachelor's degree, Applied Mathematics, Bachelor's degree, Applied Mathematics at University of California, BerkeleySummer Scholar Program, Chemistry, 4.0, Summer Scholar Program, Chemistry, 4.0 at Washington University in St. LouisMaster of Science - MS, Mechanical Engineering, Master of Science - MS, Mechanical Engineering at Carnegie Mellon UniversityHigh School, High School at Qingdao No.2 Middle School of Shandong Province
German, English, Chinese
Github Skills (31)
compressor10
auto-tuning10
pytorch10
caffe10
rounding10
intel10
python10
targeting10
acceleration10
machine-learning10
inference10
large-language-models10
numpy10
pruning10
deep-learning10
Programming languages (1)
Github contributions (5)
yintong-lu/pytorch
Oct 2024 - Jan 2025
Tensors and Dynamic neural networks in Python with strong GPU acceleration
Contributions:20 pushes, 1 branch in 2 months
intel/auto-round
Mar 2024 - Sep 2024
Advanced Quantization Algorithm for LLMs/VLMs.
Contributions:17 reviews, 18 PRs, 93 pushes in 6 months
awqgptqint4neural-compressorquantization
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