Wei Jin
Assistant Professor at Emory University
Atlanta, Georgia, United States
Summary
🤩
Rockstar🎓
Top SchoolWei Jin is an Assistant Professor at Emory University with seven years of experience bridging machine learning research and applied science, particularly in graph neural networks and adversarial robustness. He earned a PhD in Computer Science from Michigan State (4.0 GPA) after top undergraduate performance at Zhejiang University, and has interned as an applied scientist and research intern at Amazon and Snap. His contributions to open-source adversarial tooling—implementing graph attack methods in the widely used DeepRobust PyTorch library—reflect a practical focus on attacks and defenses for graph-structured data. Wei combines rigorous academic work with industry experience deploying ML at scale, and is based in Atlanta where he continues to advance robust graph learning methods.
7 years of coding experience
1 year of employment as a software developer
Doctor of Philosophy - PhD, Computer Science, 4.0/4.0, Doctor of Philosophy - PhD, Computer Science, 4.0/4.0 at Michigan State UniversityBachelor's degree, Electronic Information Engineering, 3.90/4.0, Bachelor's degree, Electronic Information Engineering, 3.90/4.0 at Zhejiang University
Github Skills (5)
pytorch10
machine-learning10
adversarial-attacks10
deep-learning10
graph-neural-network10
Programming languages (2)
Github contributions (5)
DSE-MSU/DeepRobust
Dec 2019 - Jan 2023
A pytorch adversarial library for attack and defense methods on images and graphs
Role in this project:
ML Engineer
ML EngineerContributions:256 commits, 25 PRs, 230 pushes in 3 years
Contributions summary:Wei implemented graph attack methods within the PyTorch adversarial library, focusing on adversarial attacks and defenses for graphs. The contributions involve the addition of new graph attack techniques such as graph attack fgsm, RND graph attack, and the inclusion of the DICE (delete internally, connect externally) attack method. The commits involve modifying existing files, and creating new test and attack files within the graph directory, indicating a focus on expanding the library's capabilities in adversarial graph learning.
pytorchadversarial-attacksgraph-convolutional-networksdeep-learningadversarial
ChandlerBang/AutoSSL
Jun 2021 - Jul 2022
Contributions:8 commits, 7 pushes, 1 branch in 1 year 1 month
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.