Chao Deng is an AI engineer with a decade of experience building and optimizing large-scale deep learning platforms and distributed training algorithms, currently working at Tencent after prior senior engineering work at Alibaba. He holds a PhD in Computer Science from Tsinghua University and has deep domain expertise in CTR prediction algorithms and platforms supporting tens to hundreds of billions of parameters. His background spans production systems and applied research, from designing Hadoop/ELK/Kafka-based big data platforms at Bank of China to leading capacity modeling and operational analytics. An active open-source contributor, he has improved developer tooling and front-end UIs across notable projects—ranging from a Vue3 admin suite to IntelliJ/Android Studio plugins and Android instrumentation frameworks. Colleagues appreciate that he blends rigorous academic training with hands-on bug fixes and UX improvements, often surfacing practical fixes that improve developer productivity. Based in Haidian, Beijing, he combines system-level thinking with product-aware execution to move large ML systems from research to production.
10 years of coding experience
5 years of employment as a software developer
Doctor of Philosophy, Computer Science and Technology, Doctor of Philosophy, Computer Science and Technology at Tsinghua University
Bachelor of Science, Computer Science and Technology, Honor School, Bachelor of Science, Computer Science and Technology, Honor School at Harbin Institute of Technology
A plugin for Intellj IDEA & Android Studio which can help you generate interfaces and classes of MVP. 一款Intellj IDEA 和Android Studio 自动生成MVP模式所需接口以及实现类的插件。
Role in this project:
Software Engineer
Contributions:23 commits, 5 PRs, 8 comments in 1 year 5 months
Contributions summary:Chao primarily contributed to the development of a plugin for IntelliJ IDEA and Android Studio, focusing on generating MVP (Model-View-Presenter) interfaces and classes. Their work involved refactoring code to correctly locate root directories, ensuring the proper generation of contract, model, and presenter files. Key improvements included fixing issues related to Java 8 features and addressing modifier exceptions, and improving the user interface.
Contributions:18 commits, 1 PR, 1 comment in 5 days
Contributions summary:Chao primarily focused on modifying the Android application's code, specifically within the context of an instrumentation framework. Their contributions included formatting and updating core application files, as well as adding comments to code for clarity. The user also worked on adapting the application's behavior, by including code for testing hooks, modifying parameters and configurations. These changes suggest a focus on application testing and debugging, leveraging the underlying andhook instrumentation framework.
instrumentationandroiddynamic-instrumentation
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