Yuduo W
Senior Engineering Manager at Qualcomm
San Francisco Bay Area United States
Summary
🤩
Rockstar🎓
Top SchoolYuduo W is a Senior Engineering Manager in the San Francisco Bay Area with 12 years of experience building high-performance machine learning systems, compilers, and inference stacks across mobile and datacenter platforms. Having led ML systems work at Apple and now Qualcomm, they specialize in making ML workloads run efficiently on diverse hardware—from CPUs to Neural Engines—and bridging research to production. Earlier roles at NovuMind, IBM, and UC Davis reflect deep expertise in distributed deep learning, GPU graph analytics (contributing to the Gunrock project), and cloud AI platforms. Open-source contributions to coremltools and tf-coreml demonstrate practical experience in model conversion and clear technical documentation for neural network specifications. Yuduo combines hands-on engineering with technical leadership, often surfacing under-the-hood protocol and protobuf clarity that improves long-term maintainability. Based in the Bay Area, they pair academic rigor (MS ECE, UC Davis) with a track record of shipping scalable ML infrastructure.
12 years of coding experience
12 years of employment as a software developer
Master of Science - MS, Electrical and Computer Engineering, Master of Science - MS, Electrical and Computer Engineering at University of California, Davis
English, Chinese, Chinese
Stackoverflow
1reputation
0reached
0answers
0questions
Github Skills (11)
neural-network10
machine-learning10
model-conversion10
tensorflow10
python10
coreml10
documentation10
protocol-buffers9
mozilla-deepspeech9
jupyter-notebook8
pytorch8
Programming languages (7)
Github contributions (5)
apple/coremltools
Jun 2019 - Aug 2020
Core ML tools contain supporting tools for Core ML model conversion, editing, and validation.
Role in this project:
ML Engineer
ML EngineerContributions:4 releases, 119 reviews, 101 commits in 1 year 3 months
Contributions summary:Yuduo's commits primarily focused on updating the documentation for the Core ML tools, specifically regarding the neural network specification. The code changes included detailed descriptions and explanations of different layer types, input mappings, and activation functions within the Core ML framework, and included new functionality in the protobuf files. The updates suggest an effort to clarify the structure and functionality of neural networks within the Core ML environment.
pytorchmodel-conversionvalidationdeep-learningmachine-learning
tf-coreml/tf-coreml
Jul 2019 - Jan 2020
TensorFlow to CoreML Converter
Role in this project:ML Engineer
ML EngineerContributions:2 releases, 20 commits, 17 PRs in 6 months
Contributions summary:Yuduo contributed to the repository by adding an example for converting a DeepSpeech model to Core ML format. This involved modifying existing code to incorporate the DeepSpeech model and its conversion process. The contributions demonstrate the user's focus on integrating and utilizing machine learning models with the tfcoreml converter, showcasing an understanding of model conversion workflows.
coremltensorflowconverter
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