Tan Ming is a Senior Product Manager with 10 years of cross-disciplinary experience building data- and systems-driven products across ad tech and logistics, currently leading product at TikTok for Business and Pangle. He blends a strong technical foundation—contributions to high-profile open-source projects like Swoole and Didi’s rdebug, where he optimized HTTP cookie parsing and Docker/Linux-compatible debugging tooling—with product strategy and execution. Comfortable working at the intersection of backend engineering, DevOps, and data, he has a track record of shipping robust infrastructure improvements that improve reliability and developer productivity. His background in engineering and research (NTU and Imperial College) and hands-on roles at Grab, Shopee, and Ninja Van give him domain fluency in geo, routing, and data platforms. Notably, he pairs product intuition with code-level credibility, enabling faster decision cycles with engineering teams. He also brings leadership experience from student governance and international project delivery, reflecting strong stakeholder management and operational rigor.
10 years of coding experience
5 years of employment as a software developer
Bachelor's degree, Bioengineering and Biomedical Engineering, Bachelor's degree, Bioengineering and Biomedical Engineering at Imperial College London
A levels, H1General Paper, H2 Biology, H2 Chemistry, H2 Mathematics, H2 Economics, H1 Project Work, H2 Physics, A levels, H1General Paper, H2 Biology, H2 Chemistry, H2 Mathematics, H2 Economics, H1 Project Work, H2 Physics at National Junior College
Master of Science in Technology Management, Renaissance Engineering Programme, Master of Science in Technology Management, Renaissance Engineering Programme at Nanyang Technological University Singapore
Contributions:6 releases, 33 commits, 5 PRs in 10 months
Contributions summary:Tan primarily contributed to the development and maintenance of the `rdebug` project, focusing on features related to dependency management with Composer and code coverage optimization. They improved the build process, optimized the autoloader, and ensured compatibility with Linux and Docker environments. Furthermore, the user worked on integrating and configuring the Koala replayer for debugging and testing purposes.
Contributions:5 commits, 1 PR, 2 comments in 1 day
Contributions summary:Tan primarily focused on optimizing the cookie parsing functionality within the `swoole_http_server.c` file. Their contributions involved modifying the logic to handle cookie parsing, specifically addressing issues related to leading spaces and overall parsing accuracy. The user made several iterative changes, refining the code to ensure cookies are correctly parsed and processed. The changes directly impacted the performance and functionality of the HTTP server within the Swoole library.
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