Ben He
Associate Professor
Beijing, China
Summary
🤩
Rockstar🎓
Top SchoolBen He is an associate professor and privacy-computing researcher based in Beijing with eight years of professional experience and a PhD in Information Science from the University of Glasgow. He combines academic leadership at the University of Chinese Academy of Sciences with hands-on engineering, contributing backend and data-science work to the prominent open-source Primihub privacy-preserving computing platform. His technical focus includes feature engineering for privacy-aware workflows—one-hot encoding, pandas-based server-side processing, union operations for feature statistics—and integrating robust unit tests to enable secure federated model training. He has international research experience from roles at York University and the University of Glasgow, giving him a strong foundation in both theory and applied systems. Currently enrolled as a 2025 master’s student at UCAS in privacy computing research, he stays active at the intersection of academia and production-grade open source. Colleagues know him for bridging rigorous research with pragmatic implementation to make privacy technologies deployable.
8 years of coding experience
2 years of employment as a software developer
PhD, Information Science, PhD, Information Science at The University of Glasgow
Github Skills (8)
pandas10
feature-engineering10
privacy-preserving10
python10
onehot-encoding10
federated-learning9
unit-testing8
data-analysis8
Programming languages (6)
Github contributions (5)
primihub/primihub
Jun 2022 - Jul 2022
Privacy-Preserving Computing Platform 由密码学专家团队打造的开源隐私计算平台，支持多方安全计算、联邦学习、隐私求交、匿踪查询等。
Role in this project:
Back-end Developer & Data Scientist
Back-end Developer & Data ScientistContributions:13 commits, 8 pushes in 1 month
Contributions summary:Ben focused on enhancing the feature engineering components of the privacy-preserving computing platform. Their work involved updating and testing feature encoding modules, particularly for one-hot encoding, and integrating them into the system. They contributed to unit tests and server-side operations, with focus on pandas data processing and adding union operations for feature statistics, which support the privacy-preserving model training and evaluation.
partyprivate-set-intersectionmpcpsipir
cccrick/vulhub
Feb 2024 - Nov 2025
Pre-Built Vulnerable Environments Based on Docker-Compose
Contributions:12 pushes in 1 year 9 months
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