Du Shiqiao
Software Engineering Manager at GROUND Inc
Tochigi Prefecture, Japan
Summary
👤
Senior🎓
Top SchoolDu Shiqiao is a Software Engineering Manager with 15 years of experience applying machine learning and mathematical optimization to real-world problems, currently leading engineering at GROUND Inc. He combines hands-on data science and backend engineering skills—contributing to notable open-source projects like scikit-learn and improving data pipeline tooling in PyFunctional—with a strong focus on system design that reliably serves ML and optimization workloads. Formerly a data architect at freebit and GROUND, he bridges research-grade algorithms from his Computational Biology master's at Tokyo Institute of Technology into production systems. Based in Tochigi, Japan, he codes in Python and Rust and brings a practical obsession for performance and robustness, evidenced by optimizations in core ML libraries and database integration work for data pipelines.
14 years of coding experience
10 years of employment as a software developer
Master's degree, Computational Biology, Master's degree, Computational Biology at Tokyo Institute of Technology
Chinese, Japanese, English
Stackoverflow
387reputation
6kreached
2answers
8questions
Github Skills (29)
algorithms10
sqlite10
data-pipelines10
python10
data-science10
data-engineering10
scikit10
trie10
testing10
machine-learning10
data-structure10
hmmlearn10
scikit-learn10
data-structures10
functional-programming10
Programming languages (16)
Github contributions (5)
scikit-learn/scikit-learn
Jan 2012 - Oct 2012
scikit-learn: machine learning in Python
Role in this project:
Data Scientist
Data ScientistContributions:36 commits, 3 comments, 2 issues in 9 months
Contributions summary:Du contributed to the scikit-learn repository by improving computational speed in the `sklearn/mixture/dpgmm.py` file, suggesting a focus on optimization within a machine learning context. They also fixed PEP8 warnings, indicating attention to code quality. The user's commits show a development focus on HMM, including refactoring, documentation, and new function implementation.
data-analysispythonstatisticsdata-sciencelearn-machine-learning
JuliaCollections/DataStructures.jl
Sep 2021 - Sep 2021
Julia implementation of Data structures
Role in this project:Back-end Developer
Back-end DeveloperContributions:2 reviews, 7 commits, 1 PR in 1 day
Contributions summary:Du primarily contributed to the `datastructures.jl` repository by implementing and refining data structure functionalities, specifically focusing on the `Trie` data structure. Their work included fixing iteration logic for handling non-ASCII characters, adding a function to find prefixes, and adding unit tests to ensure functionality. The user also added docstrings to improve code documentation.
data-structuresimplementation-of-data-structuresdatastructuresjulia
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