Joel Chao is a Senior Staff ML Scientist with 11 years in software and 8+ years in AI, specializing in natural language understanding and recommendation systems. He has led cross-functional teams to deliver measurable business impact—e.g., boosting user duration by 30% and ad CTR by 35%—while building robust MLOps and data infrastructures that accelerated iteration and deployment. Joel blends research and production experience from Baidu and Appier to Dcard, spanning RNNs, reinforcement learning for bidding, graph representation learning, and search-to-recommendation system redesigns. An active contributor to the Keras project, he has fixed model bugs and hardened test suites, reflecting a pragmatic focus on model correctness and engineering quality. Based in New Taipei, Taiwan, he pairs a National Taiwan University CS master’s background with a track record of turning advanced ML into scalable, product-ready systems.
11 years of coding experience
10 years of employment as a software developer
Master's degree Computer Science, Master's degree Computer Science at National Taiwan University
Contributions:13 commits, 22 PRs, 354 comments in 2 years 4 months
Contributions summary:Joel primarily contributed to improving the Keras library by fixing bugs and implementing new features. Their work involved correcting the Inception V3 network and addressing zero division errors in the merge mode for 'cos'. They also worked on the test suite, particularly focusing on fixing image path errors and refactoring local tests. Their contributions span model architecture adjustments and ensuring code quality through testing.
Contributions:12 commits, 2 PRs, 11 pushes in 1 year 6 months
finetunetensorflow
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