Zheng Tang is a Software Engineer II at Microsoft with eight years of experience building and maintaining cloud-native developer tools, currently contributing to 1ES Open Source Engineering after three years on Azure Artifacts. He blends a data-science background (BS in Data Science from UCSD and ongoing MSCS) with hands-on DevOps work, notably improving error handling and dependency management in the widely used microsoft/azure-pipelines-tasks repository. Zheng has practical ML deployment experience from roles at Altum and UCSD research on edge computing, and he’s taught and mentored hundreds of students as a head tutor and instructional assistant. Comfortable moving between research, production services, and developer tooling, he seeks opportunities that bridge machine learning and data-driven systems engineering.
8 years of coding experience
5 years of employment as a software developer
Master's Degree in Computer Science & Engineering, Computer Science, Master's Degree in Computer Science & Engineering, Computer Science at Paul G. Allen School of Computer Science & Engineering
Bachelor of Science - BS, Data Science, Bachelor of Science - BS, Data Science at University of California, San Diego - Jacobs School of Engineering
IGCSE, A Levels, IGCSE, A Levels at KTJ Primary Secondary Academia Kolej Tuanku Ja'afar
Contributions:129 reviews, 121 commits, 76 PRs in 2 years 4 months
Contributions summary:Zheng primarily focused on modifying and improving the Azure Pipelines tasks, specifically around error handling and dependency management. They addressed issues related to retrieving and using package URIs across multiple tasks, which suggests a focus on build and deployment processes. The changes also included improvements to exception handling using try-catch blocks and updates to task configurations. The user contributed to the refactoring and maintenance of build tasks.
Contributions:11 pushes, 4 branches in 1 year 5 months
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