Yi Liu
Assistant Professor at Stony Brook University
Town of Brookhaven, New York, United States
Summary
🤩
Rockstar🎓
Top SchoolYi Liu is an Assistant Professor at Stony Brook University with nine years of experience at the intersection of machine learning and systems, following faculty roles at Florida State and research training at Texas A&M. He holds a PhD in Computer Science and has contributed to graph deep learning tooling—most notably refining 3D graph network implementations in the divelab/DIG library (DiG), improving models like DimeNet++, SphereNet and SchNet. His background in electronic and biomedical engineering gives him a multidisciplinary perspective that informs both algorithmic research and practical model engineering. He combines academic leadership with hands-on open-source development, emphasizing reproducible, well-documented model implementations.
9 years of coding experience
6 years of employment as a software developer
Master's degree, Biomedical Engineering, Master's degree, Biomedical Engineering at University of Science and Technology of ChinaDoctor of Philosophy - PhD, Computer Science, Doctor of Philosophy - PhD, Computer Science at Texas A&M UniversityDoctor of Philosophy - PhD, Computer Science, Doctor of Philosophy - PhD, Computer Science at Washington State University
Github Skills (9)
graph10
pytorch10
deep-learning10
3d-graphics10
graph-neural-network10
python10
3d10
self-supervised-learning9
machine-learning9
Programming languages (1)
Github contributions (5)
divelab/DIG
Dec 2020 - Apr 2021
A library for graph deep learning research
Role in this project:
ML Engineer
ML EngineerContributions:87 commits, 15 pushes in 4 months
Contributions summary:Yi's primary contributions involve updating and modifying various model implementations within the `dig` repository, a library for graph deep learning research. These updates focus on methods related to 3D graph networks, specifically modifying the `dimenetpp`, `spherenet` and `schnet` architectures. The changes encompass adjustments to model arguments, documentation, and underlying code structures, indicating an effort to enhance and refine existing methods within the framework.
explainable-mlpytorchdataminingdeep-learninggraph-deep-learning
JacobLau0513/JacobLau0513.github.io
Aug 2022 - Mar 2024
Contributions:275 pushes, 1 branch in 1 year 7 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.