Haochen Chen

New York, New York, United States

Join Prog.AI to see contacts

Summary

🤩

Rockstar

🎓

Top School

Hao Chen is a Staff Software Engineer at Meta with a decade of experience building scalable, privacy-enhancing systems used by millions. He blends deep academic rigor—a PhD in Mathematics from the University of Washington—with hands-on research and engineering roles at Microsoft and Facebook, specializing in graph and data mining. Hao authored signaldemo.live to make end-to-end encryption concepts accessible, and contributes to prominent open-source graph learning projects like DeepWalk, where he modernized compatibility and tooling. Based in Seattle, he navigates both research and production engineering, turning complex cryptography and graph algorithms into deployable, user-facing systems.

10 years of coding experience

4 years of employment as a software developer

Bachelor of Engineering (BEng), Computer Science, Bachelor of Engineering (BEng), Computer Science at Harbin Institute of Technology

Doctor of Philosophy (Ph.D.), Computer Science, Doctor of Philosophy (Ph.D.), Computer Science at Stony Brook University

English, Chinese

Github Skills (13)

scikit-learn10

graph-algorithms10

machine-learning10

gensim10

python10

data-science10

scikit10

develop9

deep-learning9

documentation8

nlp7

natural-language-processing7

algorithms7

Programming languages (2)

Jupyter NotebookPython

Github contributions (5)

phanein/deepwalk

Mar 2016 - Apr 2020

DeepWalk - Deep Learning for Graphs

Role in this project:

Back-end Developer & Data Scientist

Contributions:15 commits, 12 PRs, 14 pushes in 4 years

Contributions summary:Haochen contributed to the DeepWalk project by addressing compatibility issues with newer versions of Gensim and Scikit-learn, updating dependencies and code to accommodate the changes. They fixed an issue related to the psutil API usage and also added arguments to the scoring script to enhance functionality. Furthermore, they updated the README documentation, providing usage instructions and highlighting the compatibility requirements with different Gensim versions.

deep-learning

GTmac/HARP

Jan 2018 - May 2020

Code for the AAAI 2018 Paper "HARP: Hierarchical Representation Learning for Networks"

Contributions:13 commits, 3 PRs, 11 pushes in 2 years 3 months

representation-learning

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.

Request Free Trial