Yingwei Li
Staff Software Engineer at Google
Cupertino, California, United States
Summary
👤
Senior🎓
Top SchoolYingwei Li is a Staff Software Engineer with 11 years of experience melding research-grade computer vision and machine learning into production systems at Apple and Google. With deep expertise in Python, C/C++, and Java, he has driven GenAI initiatives for fashion and advanced 3D perception work—contributing to TensorFlow Lingvo’s DeepFusion code for LiDAR-image fusion and 3D object detection. His background spans academic research at UCSD and internships at Microsoft and Adobe, giving him a rare combination of rigorous research methods and large-scale product deployment experience. Based in Cupertino, he often bridges novel algorithms and pragmatic engineering, turning cutting-edge papers into shipping features.
11 years of coding experience
10 years of employment as a software developer
University of California San DiegoBachelor of Science (BS) Electrical and Electronics Engineering, Bachelor of Science (BS) Electrical and Electronics Engineering at University of Science and Technology of China
English, Chinese
Github Skills (8)
computer-vision10
machine-translation10
3d-object-detection10
nlp10
deep-learning10
tensorflow10
point-cloud10
python10
Programming languages (4)
Github contributions (5)
tensorflow/lingvo
Jun 2022 - Jun 2022
Lingvo
Role in this project:
ML Engineer
ML EngineerContributions:9 commits, 6 comments in 6 days
Contributions summary:Yingwei contributed to the implementation and release of DeepFusion, as evidenced by the commit messages referencing the DeepFusion paper and the associated code changes. Their work involved modifying existing library functions related to car tasks, specifically focusing on 3D object detection and point cloud processing. The changes include implementing functions related to angle prediction, residuals, and the fusion of different data modalities (LiDAR and image data).
asrtranslationctcspeech-recognitiontensorflow
LiYingwei/ShapeTextureDebiasedTraining
Oct 2020 - Sep 2021
Code and models for the paper Shape-Texture Debiased Neural Network Training (ICLR 2021)
Contributions:6 commits, 1 PR, 6 pushes in 11 months
imagenetpytorchiclrdeep-learningtraining
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