Hengzhe Zhang
PHD Student at Victoria University of Wellington
Wellington, Wellington, New Zealand
Summary
👤
Senior🎓
Top SchoolHengzhe Zhang is a PhD student in Computer Science based in Wellington, New Zealand, specializing in automated machine learning with a research focus on using genetic programming for automated feature construction. With a decade of software engineering experience and prior industry work as an algorithm engineer at Ant Group building recommendation systems for financial products, he bridges rigorous research and production-focused algorithm development. He has practical backend engineering experience in Go and AWS S3 integration, contributing to the notable open-source goofys project by modifying core configuration and API logic. Hengzhe’s profile blends deep AutoML expertise with hands-on systems work, enabling him to both prototype novel feature engineering methods and integrate them into scalable pipelines. His background across MEng and BE degrees and ongoing PhD study reflects a sustained commitment to advancing automated feature engineering from theory to practice.
10 years of coding experience
1 year of employment as a software developer
Master of Engineering - MEng, Master of Engineering - MEng at East China Normal UniversityDoctor of Philosophy - PhD, Computer Science, Doctor of Philosophy - PhD, Computer Science at Victoria University of WellingtonBachelor of Engineering - BE, Computer Science, Bachelor of Engineering - BE, Computer Science at Xiangtan University
Github Skills (9)
golang10
go10
cloud-storage10
apidoc9
aws-s39
api9
filesystem8
s3-bucket8
amazon-s38
Programming languages (13)
Github contributions (5)
kahing/goofys
Aug 2018 - Aug 2018
Role in this project:
Back-end Developer
Back-end DeveloperContributions:6 commits, 1 PR, 2 comments in 2 days
Contributions summary:Hengzhe primarily contributed to the codebase by adding and subsequently removing options related to S3 subdomain and SSL configuration. This suggests the user was involved in modifying the configuration and integration with the S3 service. The code changes focused on internal flags, API functionalities, and data structures, demonstrating an understanding of the project's core logic. The user interacted with Go programming and AWS S3 integration.
fuseawsfile-systemgoogle-cloud-storages3-bucket
hengzhe-zhang/PS-Tree
Jun 2021 - Jan 2023
An open source python library for non-linear piecewise symbolic regression based on Genetic Programming
Contributions:27 commits, 1 PR, 19 pushes in 1 year 7 months
python-librarypiecewise-linearregressionpythongenetic
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