Zeyu Huang
Visiting Researcher at Georgia Institute of Technology
Hong Kong, China
Summary
🤩
Rockstar🎓
Top SchoolZiyue Huang is a CS PhD candidate and seasoned ML/backend engineer with nine years of experience building and debugging deep learning infrastructure. They contribute to major open-source projects like Apache MXNet and Gluon-NLP, focusing on RNN internals, sparse operators, CSR optimizations, and BERT/Electra pretraining pipelines. Comfortable across model training, test-suite hardening, and hyperparameter/config fixes, they bridge research-quality code and production-ready tooling. Notably, their work on sparse embeddings and dot-product optimizations targets real-world efficiency bottlenecks that matter for large-scale NLP training. Based in the United States, Ziyue combines academic rigor with practical engineering to improve both correctness and performance in ML systems.
9 years of coding experience
5 years of employment as a software developer
Exchange/non-degree, Computer Science, 95, Exchange/non-degree, Computer Science, 95 at University of WaterlooHong Kong University of Science and Technology (HKUST)
Chinese, English
Github Skills (21)
sparse-array10
python10
sparse-matrix10
mxnet10
machine-learning10
gluon10
sparse-file10
deep-learning10
trainings10
bert10
nlp10
sparse-data10
modeling10
natural-language-understanding9
back-end-development9
Programming languages (5)
Github contributions (5)
apache/mxnet
Apr 2017 - Nov 2020
Lightweight, Portable, Flexible Distributed/Mobile Deep Learning with Dynamic, Mutation-aware Dataflow Dep Scheduler; for Python, R, Julia, Scala, Go, Javascript and more
Role in this project:
Back-end Developer & ML Engineer
Back-end Developer & ML EngineerContributions:48 commits, 61 PRs, 251 comments in 3 years 7 months
Contributions summary:Zeyu primarily contributed to improving the test suite and fixing warnings related to data shape mismatches, which indicates involvement in model training and testing. The user addressed a bug in `SequentialRNNCell.reset()`, demonstrating familiarity with the recurrent neural network components of the library. Furthermore, the user implemented and debugged various sparse operators, including those related to the sparse embedding layer, and optimized the dot product operation involving CSR matrices. These contributions suggest expertise in deep learning, sparse matrix operations, and potentially backend implementation of the core library features.
pythonschedulerdataflowmutationdata-science
dmlc/gluon-nlp
Aug 2019 - Nov 2020
NLP made easy
Role in this project:ML Engineer
ML EngineerContributions:9 reviews, 11 commits, 11 PRs in 1 year 3 months
Contributions summary:Zeyu primarily contributed to the BERT pretraining and related scripts within the Gluon NLP repository, focusing on tasks like creating pretraining data, addressing training issues, and fixing hyperparameters for models like Electra. They made bug fixes to existing code, improved logging, and updated the codebase to address specific issues. Their work involved modifying pretraining scripts and adjusting configurations for various machine-learning models, indicating a focus on model training and related optimization.
nlpmxnetnatural-language-understandingnlgnatural-language-generation
Find and Hire Top DevelopersWe’ve analyzed the programming source code of over 60 million software developers on GitHub and scored them by 50,000 skills. Sign-up on Prog,AI to search for software developers.