Song Junxiao is a PhD candidate in Optimization at HKUST with nine years of hands-on software engineering experience, blending research rigor with practical ML systems development. Based in Hong Kong, he has deep expertise in full-stack implementation and has applied it to open-source projects such as an AlphaZero-based Gomoku agent where he integrated game logic, Python 3 updates, and a PyTorch policy-value network and training pipeline. His background in electrical and computer engineering informs a methodical approach to algorithm design, model training, and end-to-end system integration. Comfortable moving between research and production code, he brings both theoretical optimization skills and pragmatic engineering to machine learning and game-AI projects.
9 years of coding experience
Hong Kong University of Science and Technology (HKUST)
An implementation of the AlphaZero algorithm for Gomoku (also called Gobang or Five in a Row)
Role in this project:
Full-stack Developer
Contributions:29 commits, 12 PRs, 25 pushes in 1 year 3 months
Contributions summary:Song appears to be a full-stack developer contributing to an AlphaZero implementation for Gomoku. Their primary contributions include the initial setup of the game logic in `game.py`, modifications for Python 3 compatibility, and the addition of a PyTorch implementation for the policy-value network. The user also re-dumped trained models and updated the training pipeline, indicating a focus on both the core game mechanics and the integration of machine learning components. These changes suggest involvement in both the backend game logic and the machine learning aspects of the project.
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