Sida Wang
Summary
🤩
RockstarSida Wang is a software leader and founder with 10 years of experience, currently serving as CEO of BuzzBreak in Beijing. He pairs product-minded entrepreneurship with hands-on engineering honed at Airbnb and through internships at LinkedIn and Tencent. Trained at Rice University (MSCS, 4.0), he has deep full-stack and mobile experience—LAMP/WAMP web stacks, Java-based Android development and practical UI work like profile-edit tooling. As an open-source ML contributor he helped harden LinkedIn’s DeText framework by fixing multi-layer LSTM crashes and adding sparse-embedding and MLP support to better handle sparse features. His early work includes large-scale client fixes (QQ for Android LED bug) and mass refactors that improved debugging efficiency, showing a knack for both low-level reliability and product-facing features. He excels at translating algorithmic rigor into shipped product value, moving from IC roles at major tech firms to startup leadership.
10 years of coding experience
Github Skills (11)
neural-network10
tensorflow210
neuralnetwork10
lstm10
nlp10
tensorflow10
deep-neural-networks10
neural-networks10
python10
classification9
machine-learning9
Programming languages (5)
Github contributions (5)
linkedin/detext
May 2020 - Nov 2020
DeText: A Deep Neural Text Understanding Framework for Ranking and Classification Tasks
Role in this project:
ML Engineer
ML EngineerContributions:2 releases, 6 reviews, 10 commits in 5 months
Contributions summary:Sida primarily contributed to the DeText framework by addressing runtime crashes in the LSTM encoder implementation and providing fixes related to multi-layer LSTM models. They enhanced the model by adding support for sparse embeddings and MLP layers to enhance the model's ability to handle and interact with sparse features. Additional contributions include correcting errors related to setup and installation with the addition of classifiers and descriptions in the setup.py file.
nlpunderstandingdeep-learningmulti-label-classificationclassification-tasks
StarWang/detext
May 2020 - Jan 2022
DeText: A Deep Neural Text Understanding Framework for Ranking and Classification Tasks
Contributions:43 pushes, 9 branches in 1 year 8 months
nlpunderstandingdeep-learningmulti-label-classificationclassification-tasks
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