Scholar
Jiong Zhu
Google Scholar ID: KjGFQ0QAAAAJ
Research Scientist, Meta
Citations & Impact
Citations
2,126
H-index
8
i10-index
8
Publications
14
Co-authors
13
list available
Publications
Resume (English only)
Academic Achievements
- 2023: 'Simplifying Distributed Neural Network Training on Massive Graphs' at ICML 2023; 2022: 'How does Heterophily Impact the Robustness of Graph Neural Networks?' at KDD 2022; 2021: 'Graph Neural Networks with Heterophily' at AAAI Conference on Artificial Intelligence, etc.
Research Experience
- Applied Scientist Intern at Amazon, focusing on training data curation and semantic-based information retrieval; Organizer of the 2nd edition of the Workshop on Graph Learning Benchmarks; Published multiple research papers on graph neural networks.
Education
- Ph.D. Candidate: University of Michigan, Computer Science and Engineering, Advisor: Danai Koutra; Master's Degree: University of Michigan, Electrical and Computer Engineering; Bachelor's Degree: Xi’an Jiaotong University, Special Class for the Gifted Young.
Background
- Research Interests: Graph Representation Learning, Graph Neural Networks (GNNs); Field: Computer Science and Engineering; Summary: Focuses on enhancing GNN performance in heterophilous graphs, addressing their limitations, robustness, scalability, and fairness in complex, large-scale environments.
Miscellany
- Tech-savvy user, often helps friends with coding and tech questions.
