I am a second year Ph.D. student (2023 Fall - Present) in Computer Science and Engineering at University of Notre Dame. I am supervised by Prof. Yanfang (Fanny) Ye and work closely with Prof. Chuxu Zhang. My research focuses on machine learning, with a particular emphasis on developing effective, efficient, and generalizable models. Currently, I am deeply engaged in designing next generation graph learning models, exploring their methodologies, theoretical basis, and applications. Specifically, the topics cover the following three aspects.

• Next-Gen Paradigm - Graph Foundation Model: transferable patterns (NeurIPS 24), structural heterogeneity (IJCAI 24), feature heterogeneity (NAACL 25), task heterogeneity (ICML 25), efficiency inference (WSDM 25).
• Next-Gen Model Architecture - Beyond Message Passing: supervised learning (ICML 25).
• Next-Gen Application - Graph + X: graph-based explanation (KDD 24, KDD 25), GraphRAG (ACL 25), social media detection (ACL 25).

If you’re interested in my research or would like to explore potential collaborations, feel free to reach out via email (zwang43 [AT] nd [DOT] edu). Looking forward to connecting!

News

• [2025.05] Two papers were accepted by ACL 2025. Congratulations to Zheyuan and Tianyi!
• [2025.05] Two tutorial proposals were accepted by KDD 25—one on [graph foundation models] and the other on graph prompt learning. Looking forward to seeing you in Toronto!
• [2025.05] Two papers were accepted by ICML 2025: (1) We developed a theory-guided task alignment on graphs via task-trees (GIT). (2) We developed GPM, a novel Transformer-based graph representation learning framework that totally goes beyond message passing.
• [2025.02] I will join Amazon as Applied Scientist Intern this Summer working with Prof. Rui Song and Dr. Qingkai Zeng.
• [2025.01] One paper was accepted by NAACL 2025. We developed TANS to synthesize textual node descriptions on graphs.
• [2024.11] One paper was accepted by KDD 2025. Congratulations to Zheyuan!
• [2024.10] One paper was accepted by WSDM 2025. We developed SimMLP, an efficient inference method on graphs!
• [2024.09] One paper was accepted by NeurIPS 2024. We developed a transferable, cross-domain, cross-task graph foundation model GFT.
• [2024.05] One paper was accepted by KDD 2024. Congratulations to Zheyuan!
• [2024.04] One paper was accepted by IJCAI 2024. We analyzed the impact of structural differences on graph transfer learning (link).
• [2024.03] Receive the Travel Award Grand from SDM 2024. Thanks SDM!

Selected Publications Full List

(* indicates equal contribution.)

Tutorial

• [KDD 25] Graph Foundation Models: Challenges, Methods, and Open Questions
  Zehong Wang, Chuxu Zhang, Jundong Li, Nitesh V Chawla, Yanfang Ye.
  [website]

• [KDD 25] Graph Prompting for Graph Learning Models: Recent Advances and Future Directions
  Xingbo Fu, Zehong Wang, Zihan Chen, Jiazheng Li, Yaochen Zhu, Zhenyu Lei, Cong Shen, Yanfang Ye, Chuxu Zhang, Jundong Li.

2025

• [ICML 25] Neural Graph Pattern Machine
  Zehong Wang, Zheyuan Zhang, Tianyi Ma, Nitesh V Chawla, Chuxu Zhang, Yanfang Ye.
  [paper]

• [ICML 25] Towards Graph Foundation Models: Learning Generalities Across Graphs via Task-trees
  Zehong Wang, Zheyuan Zhang, Tianyi Ma, Nitesh V Chawla, Chuxu Zhang, Yanfang Ye.
  [paper] [code]

• [NAACL 25 Main] Can LLMs Convert Graphs to Text-Attributed Graphs? (Oral)
  Zehong Wang, Sidney Liu, Zheyuan Zhang, Tianyi Ma, Chuxu Zhang, Yanfang Ye.
  [paper] [code]

• [WSDM 25] Training MLPs on Graphs without Supervision
  Zehong Wang, Zheyuan Zhang, Chuxu Zhang, Yanfang Ye.
  [paper] [code]

• [KDD 25] MOPI-HFRS: A Multi-objective Personalized Health-aware Food Recommendation System with LLM-enhanced Interpretation
  Zheyuan Zhang, Zehong Wang, Tianyi Ma, Varun Sameer Taneja, Sofia Nelson, Nhi Ha Lan Le, Keerthiram Murugesan, Mingxuan Ju, Nitesh V Chawla, Chuxu Zhang, Yanfang Ye.
  [paper] [code]

• [ACL 25 Main] NGQA: A Nutritional Graph Question Answering Benchmark for Personalized Health-aware Nutritional Reasoning
  Zheyuan Zhang*, Yiyang Li*, Nhi Ha Lan Le*, Zehong Wang, Tianyi Ma, et al.
  [paper] [code]

• [ACL 25 Findings] LLM-Empowered Class Imbalanced Graph Prompt Learning for Online Drug Trafficking Detection
  Tianyi Ma, Yiyue Qian, Zehong Wang, Zheyuan Zhang, Chuxu Zhang, Yanfang Ye
  [paper]

2024

• [NeurIPS 24] GFT: Graph Foundation Model with Transferable Tree Vocabulary
  Zehong Wang, Zheyuan Zhang, Nitesh V Chawla, Chuxu Zhang, Yanfang Ye.
  [paper] [code]

• [KDD 24] Diet-ODIN: A Novel Framework for Opioid Misuse Detection with Interpretable Dietary Pattern
  Zheyuan Zhang*, Zehong Wang*, Shifu Hou, Evan Hall, Landon Bachman, Jasmine White, Vincent Galassi, Nitesh V Chawla, Chuxu Zhang, Yanfang Ye.
  [paper] [code]

• [IJCAI 24] Subgraph Pooling: Tackling Negative Transfer on Graphs
  Zehong Wang, Zheyuan Zhang, Chuxu Zhang, Yanfang Ye.
  [paper] [code] [poster]

2023

• [SDM 23] Heterogeneous Graph Contrastive Multi-view Learning
  Zehong Wang, Qi Li, Donghua Yu, Xiaolong Han, Xiao-Zhi Gao, Shigen Shen.
  [paper] [code]

Services

Journal Reviewer: TMLR, TKDE, TKDD, TDSC, TBD, TNNLS

Conference Reviewer/Program Committee: NeurIPS 2025 2024, ICLR 2025 2024, ICML 2025, KDD 2025, AISTATS 2025, AAAI 2025 2024, COLING 2025 2024.

Contact

• Email: zwang43 [at] nd [dot] edu
• Office: 247 Fitzpatrick Hall of Engineering
• Location: University of Notre Dame, Notre Dame, IN 46565