Shenyang Huang
Postdoc (Research Associate) In Geometric ML For Molecular Modelling
United Kingdom
Summary
👤
Senior🎓
Top SchoolShenyang Huang is a postdoctoral researcher in geometric machine learning at the University of Oxford, specializing in temporal graph learning, link prediction, and anomaly detection on dynamic graphs. With a PhD from McGill/Mila and nine years of experience spanning academia and industry, he has contributed to state-of-the-art graph transformers and molecular property prediction (including work on GPS++ and the Graphium library). He organizes the Temporal Graph Learning Workshop at NeurIPS and runs a weekly reading group, reflecting both research leadership and community-building. His applied work includes accelerating large graph models on IPUs and integrating transformer architectures into recommender systems, with open-source contributions to PyTorch Geometric. Combining deep theoretical grounding with practical engineering, he bridges molecular modelling, continual learning, and scalable GNN/transformer systems.
9 years of coding experience
2 years of employment as a software developer
High School IB Diploma, High School IB Diploma at Rothesay Netherwood SchoolDoctor of Philosophy - PhD Computer Science, Doctor of Philosophy - PhD Computer Science at McGill University
English, Chinese, French
Github Skills (9)
jekyll9
bootstrap9
static-site9
sass8
jekyll-theme8
liquid7
visualization6
static-site-generator6
foundation-models1
Programming languages (5)
Github contributions (5)
shenyangHuang/LAD
May 2020 - Nov 2021
Contributions:32 commits, 28 pushes, 2 branches in 1 year 5 months
shenyangHuang/TGB
May 2023 - Mar 2025
Temporal Graph Benchmark project repo
Contributions:10 releases, 1 review, 35 PRs in 1 year 10 months
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.