Anson Wong
Senior Software Engineer at Cruise
Sunnyvale, California, United States
Summary
🤩
Rockstar🎓
Top SchoolAnson Wong is a Senior Software Engineer with 11 years of experience building simulation and robotics systems, currently working on autonomous vehicle simulation at Cruise in Sunnyvale. He has deep expertise in robot simulation, ROS/ROS2, high-performance computing, and container orchestration from multiple roles at AWS and academic research in deep reinforcement learning. Anson contributes to open-source RL tooling—implementing MLP/CNN models, layer normalization, and image-environment wrappers in the well-regarded garage RL toolkit—bridging research and production needs. Fluent in Cantonese, Mandarin, and English, he combines strong systems engineering with hands-on ML experience and a track record of shipping simulator plugins and ROS integrations. His background spans industry and academia, including a CS master’s from USC and cross-continental research roles that inform pragmatic, reproducible simulation work.
11 years of coding experience
7 years of employment as a software developer
Master's degree Computer Science, Master's degree Computer Science at University of Southern CaliforniaThe University of Hong Kong (HKU)Exchange student Computer Science, Exchange student Computer Science at The University of North Carolina at Chapel Hill
Chinese, English, 普通話
Github Skills (11)
algorithm10
mask-rcnn10
faster-rcnn10
machine-learning10
tensorflow10
mlp10
python10
pytest9
repr9
pytorch9
rep9
Programming languages (11)
Github contributions (5)
rlworkgroup/garage
Oct 2018 - Aug 2020
A toolkit for reproducible reinforcement learning research.
Role in this project:
ML Engineer
ML EngineerContributions:1 release, 96 commits, 178 PRs in 1 year 9 months
Contributions summary:Anson implemented and tested Multi-Layer Perceptron (MLP) and Convolutional Neural Network (CNN) models, along with the relevant unit tests. They added functionality for layer normalization within MLPs and expanded the test suite. The user also added gym.Env wrappers, particularly for image-based environments, including resizing, grayscale conversion, and frame stacking. The user made modifications to address code style issues and added RL2 support.
pytorchreinforcement-learningreproduciblereproducibilityrl-algorithms
ahtsan/ahtsan.github.io
Apr 2017 - Dec 2024
Contributions:47 pushes, 1 branch in 7 years 9 months
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