Juntao Li is a software engineer with 7 years of experience building high-performance distributed systems and applied AI, currently contributing to Google's Ads storage infrastructure from San Bruno. He blends a strong research background in computer vision and reinforcement learning—earned at Carnegie Mellon and Zhejiang University—with hands-on engineering experience at Splunk and SenseTime. Juntao has a track record of shipping impactful optimizations, from halving customer dashboard build time at Splunk to implementing large-scale timer and pop-consumption improvements in the widely used Apache RocketMQ project. His research produced practical wins too, including a traffic gesture recognition pipeline with a 89.7% accuracy and an OGTL reinforcement-learning scheme that dramatically cut training time. Equally comfortable in low-level distributed storage and ML model development, he often bridges the gap between prototype research and production-ready systems. Colleagues describe him as a pragmatic problem-solver who accelerates labeling and training workflows and roots solutions in measurable performance gains.
7 years of coding experience
2 years of employment as a software developer
Master's degree, Computer Science, Master's degree, Computer Science at Carnegie Mellon University
Bachelor of Engineering - BE, Computer Software Engineering, Bachelor of Engineering - BE, Computer Software Engineering at Zhejiang University
Apache RocketMQ is a cloud native messaging and streaming platform, making it simple to build event-driven applications.
Role in this project:
Back-end Developer
Contributions:81 reviews, 3 commits, 26 PRs in 19 days
Contributions summary:Juntao primarily contributed to the Apache RocketMQ project by implementing and refining features related to the timer message store, including support for arbitrary time delays. They addressed review feedback, optimized existing code, and resolved bugs. Furthermore, the user made substantial contributions to improving the pop consumption mode, replacing scheduled messages with timer messages and optimizing the CK/ACK process. They also worked on optimizing the HA process and addressing potential data inconsistencies.
Contributions:22 commits, 19 pushes, 1 branch in 12 days
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