Zheng Zhang
Professor, Chief Scientist At HKU-SH X-Lab at The University of Hong Kong
Shanghai, Shanghai, China
Summary
🤩
Rockstar🎓
Top SchoolZheng Zhang is a seasoned AI researcher and engineering leader with over two decades of experience spanning academic and industry labs, currently serving as Professor and Chief Scientist at HKU-SH X-Lab and a professor at NYU Shanghai. He has led major research efforts at Microsoft Research Asia and founded the System Research Group, later directing AWS’s Shanghai AI Lab where he bridged cutting-edge research and product-scale AI. His technical contributions include core graph neural network work in the popular DGL project, enabling message passing and tensor integration that underpin modern graph deep learning. Trained with a PhD from UIUC and early roots at Fudan, he blends deep systems expertise with practical ML engineering and a track record of building research teams that translate theory into real-world AI systems.
11 years of coding experience
25 years of employment as a software developer
Master of Engineering - MEng, Master of Engineering - MEng at The University of Texas at DallasBachelor's degree Electrical and Electronics Engineering, Bachelor's degree Electrical and Electronics Engineering at Fudan UniversityDoctor of Philosophy - PhD Computer Engineering, Doctor of Philosophy - PhD Computer Engineering at University of Illinois Urbana-Champaign
Github Skills (13)
tensorrt10
pytorch10
machine-learning10
tensor10
deep-learning10
networkx10
tensorflow10
graph-neural-network10
operation10
python10
algorithms8
algorithm8
object-oriented-programming8
Programming languages (5)
Github contributions (5)
dmlc/dgl
Apr 2018 - Jun 2018
Python package built to ease deep learning on graph, on top of existing DL frameworks.
Role in this project:
ML Engineer
ML EngineerContributions:30 commits, 12 PRs, 37 pushes in 2 months
Contributions summary:Zheng primarily worked on developing and implementing graph neural network functionalities within the DGL framework. Their commits introduced a `mx_Graph` class that integrates with `networkx` and supports message passing, update, and readout functions. They further expanded the system to work with tensors and neural networks, enabling the construction of graph neural network models. The user's work significantly contributed to the core components of graph deep learning within the project.
pytorchpythondeep-learningmachine-learninggraph-neural-networks
zzhang-cn/ICS-NYUSH
Jan 2017 - Mar 2018
Contributions:15 commits, 2 PRs, 13 pushes in 1 year 2 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.