Jiong Zhu

Research Scientist, Facebook

Joined

December 2019

Names

Jiong Zhu (Preferred)

Emails

****@umich.edu (Confirmed)

****@amazon.com (Confirmed)

****@meta.com (Confirmed)

Personal Links

Career & Education History

Research Scientist

Facebook (meta.com)

2025 – Present

Applied Scientist

Amazon (amazon.com)

2024 – 2025

Applied Scientist Intern

Amazon (amazon.com)

2022 – 2024

PhD student

University of Michigan (umich.edu)

2019 – 2024

Research Intern

Adobe Systems (adobe.com)

2020 – 2020

Advisors, Relations & Conflicts

PhD Advisor

Danai Koutra

2019 – 2024

Expertise

Large Language Model

2023 – Present

Recommendation System

2023 – Present

Graph Neural Network

2019 – Present

Heterophily

2019 – Present

Publications

Learning Laplacian Positional Encodings for Heterophilous Graphs
Michael Ito, Jiong Zhu, Dexiong Chen, Danai Koutra, Jenna Wiens
- AISTATS 2025 Poster
- Readers: Everyone
On the Impact of Feature Heterophily on Link Prediction with Graph Neural Networks
Jiong Zhu, Gaotang Li, Yao-An Yang, Jing Zhu, Xuehao Cui, Danai Koutra
- NeurIPS 2024 poster
- Readers: Everyone
On Performance Discrepancies Across Local Homophily Levels in Graph Neural Networks
Donald Loveland, Jiong Zhu, Mark Heimann, Benjamin Fish, Michael T Schaub, Danai Koutra
- LoG 2023 Oral
- Readers: Everyone
Simplifying Distributed Neural Network Training on Massive Graphs: Randomized Partitions Improve Model Aggregation
Jiong Zhu, Aishwarya Naresh Reganti, Edward W Huang, Charles Andrew Dickens, Nikhil Rao, Karthik Subbian, Danai Koutra
- ICML LLW 2023
- Readers: Everyone
On Performance Discrepancies Across Local Homophily Levels in Graph Neural Networks
Donald Loveland, Jiong Zhu, Mark Heimann, Benjamin Fish, Michael T. Schaub, Danai Koutra
- Published: 01 Jan 2023, Last Modified: 18 Oct 2023
- CoRR 2023
- Readers: Everyone
Simplifying Distributed Neural Network Training on Massive Graphs: Randomized Partitions Improve Model Aggregation
Jiong Zhu, Aishwarya Reganti, Edward W. Huang, Charles Dickens, Nikhil Rao, Karthik Subbian, Danai Koutra
- Published: 01 Jan 2023, Last Modified: 18 Oct 2023
- CoRR 2023
- Readers: Everyone
The 3rd Workshop on Graph Learning Benchmarks (GLB 2023)
Jiaqi Ma, Jiong Zhu, Yuxiao Dong, Danai Koutra, Jingrui He, Qiaozhu Mei, Anton Tsitsulin, Xingjian Zhang, Marinka Zitnik
- Published: 01 Jan 2023, Last Modified: 18 Oct 2023
- KDD 2023
- Readers: Everyone
How does Heterophily Impact the Robustness of Graph Neural Networks?: Theoretical Connections and Practical Implications
Jiong Zhu, Junchen Jin, Donald Loveland, Michael T. Schaub, Danai Koutra
- 2022 (modified: 25 Jan 2023)
- KDD 2022
- Readers: Everyone
On Graph Neural Network Fairness in the Presence of Heterophilous Neighborhoods
Donald Loveland, Jiong Zhu, Mark Heimann, Ben Fish, Michael T. Schaub, Danai Koutra
- 2022 (modified: 25 Jan 2023)
- CoRR 2022
- Readers: Everyone
On the Relationship between Heterophily and Robustness of Graph Neural Networks
Jiong Zhu, Junchen Jin, Donald Loveland, Michael T Schaub, Danai Koutra
- Published: 28 Jan 2022, Last Modified: 13 Feb 2023
- ICLR 2022 Submitted
- Readers: Everyone

View all 15 publications

Co-Authors

View all 41 co-authors