Laura Wang
Software Engineer at Meta
Bellevue, Washington, United States
Summary
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Rockstar🎓
Top SchoolLaura Wang is a software engineer and GPU computing specialist with 12 years of experience, currently at Meta after research scientist work at ByteDance and applied scientist roles at AWS and Amazon. She holds advanced degrees from UC Davis (Ph.D. candidate in Computer Science) and a B.A.Sc. from Zhejiang University, with a long-standing focus on GPGPU, parallel algorithms, and implementing classic algorithms at large GPU scale. Her open-source contributions include performance-oriented work on the widely used TVM compiler and NNVM framework, where she optimized CUDA kernels for ResNet and MobileNet and implemented critical activations and benchmarking tools. Combining deep academic research with production ML engineering, she brings both low-level GPU optimization expertise and practical experience shipping ML systems at scale. An understated strength is her cross-cultural research background—from Zhejiang and National Chiao Tung University exchanges to internships at DARPA and NEC—that sharpens her collaborative, systems-first approach.
12 years of coding experience
7 years of employment as a software developer
Doctor of Philosophy (Ph.D.) Computer Science, Doctor of Philosophy (Ph.D.) Computer Science at University of California, DavisBachelor of Applied Science (B.A.Sc.) Electrical and Electronics Engineering, Bachelor of Applied Science (B.A.Sc.) Electrical and Electronics Engineering at Zhejiang University
Chinese, English, Japanese
Stackoverflow
1reputation
0reached
0answers
0questions
Github Skills (19)
benchmark10
python10
machine-learning10
benchmarking10
mask-rcnn10
deeplearning-ai10
compiler-compiler10
deep-learning10
gpu10
cuda10
compiler10
faster-rcnn10
tensor10
performance-monitor9
convolutional-neural-networks9
Programming languages (8)
Github contributions (5)
apache/tvm
Jul 2017 - Oct 2021
Open deep learning compiler stack for cpu, gpu and specialized accelerators
Role in this project:
ML Engineer
ML EngineerContributions:58 reviews, 72 commits, 91 PRs in 4 years 3 months
Contributions summary:Laura's primary contributions involve developing and optimizing machine learning models, specifically for the TVM deep learning compiler stack. The commits demonstrate a focus on implementing and scheduling CUDA-based kernels, especially for convolutional neural networks, highlighting optimization efforts for ResNet and MobileNet architectures. The user also migrated and tested softmax and relu activation functions, indicating the development of essential building blocks for neural networks.
metalvulkancompilertensoropencl
dmlc/nnvm
Sep 2017 - May 2018
Role in this project:ML Engineer
ML EngineerContributions:5 commits, 3 PRs, 6 comments in 7 months
Contributions summary:Laura contributed to the development and benchmarking of deep learning models within the NNVM framework. Their work involved integrating and testing example models, specifically focusing on ResNet and MobileNet for image classification on GPUs. They also implemented and optimized a CUDA-based benchmarking script to evaluate the performance of these models. Furthermore, the user addressed specific issues related to the implementation of convolutional layers.
cudametalcomputation-graphtvmdeep-learning
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