Zehong Wang
Portrait
Ph.D. Candidate
Computer Science and Engineering
Logo University of Notre Dame

I am a third year Ph.D. student (2023 Fall - Present) in Computer Science and Engineering at University of Notre Dame advised by Prof. Yanfang (Fanny) Ye. My research focuses on developing generalizable AI systems that integrate multimodal data for scientific discovery. Recently, I have been working on scientific foundation models and AI agents, with the goal of building AI scientists for drug discovery and public health.

Feel free to reach out me via email, wechat, or linkedin if you have any questions, explore potential collaborations, or just for talk! 😊

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News
2026
📚 Our survey on weight space learning is released.
Mar 09
One paper (TreeDiff) accepted by WWW 2026. This is my first corresponding paper 😊.
Jan 12
One paper (LAMI) accepted by EACL 2026. Congrets to Yiyang Li!
Jan 03
2025
📚 Our survey on LLM for cross-disciplinary research is released.
Sep 22
Two papers (G2PM, AutoData) accepted by NeurIPS 2025.
Sep 19
💼 I will join Amazon as Applied Scientist Intern working with Prof. Rui Song, Prof. Sheng Wang and Dr. Qingkai Zeng.
May 21
📚 Our survey on graph foundation model is released.
May 20
Two papers (NGQA, LLM-HetGDT) accepted by ACL 2025.
May 14
📖 Two tutorials accepted by KDD 25 (graph foundation model and graph prompt learning).
May 05
Two papers (GPM, GIT) accepted by ICML 2025.
Apr 30
2025
One paper (TANS) accepted by NAACL 2025.
Jan 21
2024
One paper (MOPI-HFRS) accepted by KDD 2025. Congrets to Zheyuan Zhang!
Nov 14
One paper (SimMLP) accepted by WSDM 2025.
Oct 22
One paper (GFT) accepted by NeurIPS 2024.
Sep 14
One paper (Diet-ODIN) accepted by KDD 2024. Congrets to Zheyuan Zhang!
May 15
One paper (Subgraph Pooling) accepted by IJCAI 2024.
Apr 14
Receive the Travel Award Grand from SDM 2024. Thanks SDM!
Mar 14
Surveys & Tutorials (view all )
A Survey of Weight Space Learning: Understanding, Representation, and Generation
A Survey of Weight Space Learning: Understanding, Representation, and Generation

Xiaolong Han*, Zehong Wang*, Bo Zhao, Binchi Zhang, Jundong Li, Damian Borth, Rose Yu, Haggai Maron, Yanfang Ye, Lu Yin, Ferrante Neri (* equal contribution, corresponding author)

arXiv preprint 2026 Survey

[Paper] [Repo]

A Survey of Weight Space Learning: Understanding, Representation, and Generation

Xiaolong Han*, Zehong Wang*, Bo Zhao, Binchi Zhang, Jundong Li, Damian Borth, Rose Yu, Haggai Maron, Yanfang Ye, Lu Yin, Ferrante Neri (* equal contribution, corresponding author)

arXiv preprint 2026 Survey

[Paper] [Repo]

LLMs4All: A Review on Large Language Models for Research and Applications in Academic Disciplines
LLMs4All: A Review on Large Language Models for Research and Applications in Academic Disciplines

Yanfang Ye, Zheyuan Zhang*, Tianyi Ma*, Zehong Wang*, Yiyang Li*, Shifu Hou*, Weixiang Sun*, Kaiwen Shi*, Yijun Ma*, Wei Song, Ahmed Abbasi, Ying Cheng, Jane Cleland-Huang, Steven Corcelli, Robert Goulding, Ming Hu, Ting Hua, John Lalor, Fang Liu, Tengfei Luo, Ed Maginn, Nuno Moniz, Jason Rohr, Brett Savoie, Daniel Slate, Tom Stapleford, Matthew Webber, Olaf Wiest, Johnny Zhang, Nitesh V. Chawla (* equal contribution)

arXiv preprint 2025 Survey

[Paper]

LLMs4All: A Review on Large Language Models for Research and Applications in Academic Disciplines

Yanfang Ye, Zheyuan Zhang*, Tianyi Ma*, Zehong Wang*, Yiyang Li*, Shifu Hou*, Weixiang Sun*, Kaiwen Shi*, Yijun Ma*, Wei Song, Ahmed Abbasi, Ying Cheng, Jane Cleland-Huang, Steven Corcelli, Robert Goulding, Ming Hu, Ting Hua, John Lalor, Fang Liu, Tengfei Luo, Ed Maginn, Nuno Moniz, Jason Rohr, Brett Savoie, Daniel Slate, Tom Stapleford, Matthew Webber, Olaf Wiest, Johnny Zhang, Nitesh V. Chawla (* equal contribution)

arXiv preprint 2025 Survey

[Paper]

Graph Foundation Models: A Comprehensive Survey
Graph Foundation Models: A Comprehensive Survey

Zehong Wang*, Zheyuan Liu*, Tianyi Ma*, Jiazheng Li*, Zheyuan Zhang*, Xingbo Fu*, Yiyang Li*, Zhengqing Yuan*, Wei Song, Yijun Ma, Qingkai Zeng, Xiusi Chen, Jianan Zhao, Jundong Li, Meng Jiang, Pietro Lio, Nitesh Chawla, Chuxu Zhang, Yanfang Ye (* equal contribution, corresponding author)

arXiv preprint 2025 Survey

[Paper] [Repo]

Graph Foundation Models: A Comprehensive Survey

Zehong Wang*, Zheyuan Liu*, Tianyi Ma*, Jiazheng Li*, Zheyuan Zhang*, Xingbo Fu*, Yiyang Li*, Zhengqing Yuan*, Wei Song, Yijun Ma, Qingkai Zeng, Xiusi Chen, Jianan Zhao, Jundong Li, Meng Jiang, Pietro Lio, Nitesh Chawla, Chuxu Zhang, Yanfang Ye (* equal contribution, corresponding author)

arXiv preprint 2025 Survey

[Paper] [Repo]

Graph Prompting for Graph Learning Models: Recent Advances and Future Directions
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

ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD) 2025 Tutorial

[Paper] [Website]

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

ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD) 2025 Tutorial

[Paper] [Website]

Graph Foundation Models: Challenges, Methods, and Open Questions
Graph Foundation Models: Challenges, Methods, and Open Questions

Zehong Wang, Chuxu Zhang, Jundong Li, Nitesh Chawla, Yanfang Ye

ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD) 2025 Tutorial

[Paper] [Website]

Graph Foundation Models: Challenges, Methods, and Open Questions

Zehong Wang, Chuxu Zhang, Jundong Li, Nitesh Chawla, Yanfang Ye

ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD) 2025 Tutorial

[Paper] [Website]

All publications
Selected Publications (view all )
Policy4OOD: A Knowledge-Guided World Model for Policy Intervention Simulation against the Opioid Overdose Crisis
Policy4OOD: A Knowledge-Guided World Model for Policy Intervention Simulation against the Opioid Overdose Crisis

Yijun Ma*, Zehong Wang*, Weixiang Sun, Zheyuan Zhang, Kaiwen Shi, Nitesh Chawla, Yanfang Ye (* equal contribution)

arXiv preprint 2026

[Paper]

Policy4OOD: A Knowledge-Guided World Model for Policy Intervention Simulation against the Opioid Overdose Crisis

Yijun Ma*, Zehong Wang*, Weixiang Sun, Zheyuan Zhang, Kaiwen Shi, Nitesh Chawla, Yanfang Ye (* equal contribution)

arXiv preprint 2026

[Paper]

Temporal Graph Pattern Machine
Temporal Graph Pattern Machine

Yijun Ma*, Zehong Wang*, Weixiang Sun, Yanfang Ye (* equal contribution, corresponding author)

arXiv preprint 2026

[Paper] [Code]

Temporal Graph Pattern Machine

Yijun Ma*, Zehong Wang*, Weixiang Sun, Yanfang Ye (* equal contribution, corresponding author)

arXiv preprint 2026

[Paper] [Code]

Molecular Representations in Implicit Functional Space via Hyper-Networks
Molecular Representations in Implicit Functional Space via Hyper-Networks

Zehong Wang*, Xiaolong Han*, Qi Yang*, Xiangru Tang, Fang Wu, Xiaoguang Guo, Weixiang Sun, Tianyi Ma, Pietro Lio, Le Cong, Sheng Wang, Chuxu Zhang, Yanfang Ye (* equal contribution)

arXiv preprint 2026

[Paper] [Code]

Molecular Representations in Implicit Functional Space via Hyper-Networks

Zehong Wang*, Xiaolong Han*, Qi Yang*, Xiangru Tang, Fang Wu, Xiaoguang Guo, Weixiang Sun, Tianyi Ma, Pietro Lio, Le Cong, Sheng Wang, Chuxu Zhang, Yanfang Ye (* equal contribution)

arXiv preprint 2026

[Paper] [Code]

Why Reasoning Fails to Plan: A Planning-Centric Analysis of Long-Horizon Decision Making in LLM Agents
Why Reasoning Fails to Plan: A Planning-Centric Analysis of Long-Horizon Decision Making in LLM Agents

Zehong Wang, Fang Wu, Hongru Wang, Xiangru Tang, Bolian Li, Zhenfei Yin, Yijun Ma, Yiyang Li, Weixiang Sun, Xiusi Chen, Yanfang Ye

arXiv preprint 2026

[Paper] [Code]

Why Reasoning Fails to Plan: A Planning-Centric Analysis of Long-Horizon Decision Making in LLM Agents

Zehong Wang, Fang Wu, Hongru Wang, Xiangru Tang, Bolian Li, Zhenfei Yin, Yijun Ma, Yiyang Li, Weixiang Sun, Xiusi Chen, Yanfang Ye

arXiv preprint 2026

[Paper] [Code]

Controllable Graph Generation with Diffusion Models via Inference-Time Tree Search Guidance
Controllable Graph Generation with Diffusion Models via Inference-Time Tree Search Guidance

Jiachi Zhao*, Zehong Wang*, Yamei Liao, Chuxu Zhang, Yanfang Ye (* equal contribution, corresponding author)

The Web Conference (WWW) 2026

[Paper] [Code]

Controllable Graph Generation with Diffusion Models via Inference-Time Tree Search Guidance

Jiachi Zhao*, Zehong Wang*, Yamei Liao, Chuxu Zhang, Yanfang Ye (* equal contribution, corresponding author)

The Web Conference (WWW) 2026

[Paper] [Code]

Interpretable Graph-Language Modeling for Detecting Youth Illicit Drug Use
Interpretable Graph-Language Modeling for Detecting Youth Illicit Drug Use

Yiyang Li*, Zehong Wang*, Zhengqing Yuan, Zheyuan Zhang, Keerthiram Murugesan, Chuxu Zhang, Yanfang Ye (* equal contribution)

Conference of the European Chapter of the Association for Computational Linguistics (EACL) 2026

[Paper] [Code]

Interpretable Graph-Language Modeling for Detecting Youth Illicit Drug Use

Yiyang Li*, Zehong Wang*, Zhengqing Yuan, Zheyuan Zhang, Keerthiram Murugesan, Chuxu Zhang, Yanfang Ye (* equal contribution)

Conference of the European Chapter of the Association for Computational Linguistics (EACL) 2026

[Paper] [Code]

Generative Graph Pattern Machine
Generative Graph Pattern Machine

Zehong Wang, Zheyuan Zhang, Tianyi Ma, Chuxu Zhang, Yanfang Ye

Annual Conference on Neural Information Processing Systems (NeurIPS) 2025

[Paper] [Code]

Generative Graph Pattern Machine

Zehong Wang, Zheyuan Zhang, Tianyi Ma, Chuxu Zhang, Yanfang Ye

Annual Conference on Neural Information Processing Systems (NeurIPS) 2025

[Paper] [Code]

Beyond Message Passing: Neural Graph Pattern Machine
Beyond Message Passing: Neural Graph Pattern Machine

Zehong Wang, Zheyuan Zhang, Tianyi Ma, Nitesh V Chawla, Chuxu Zhang, Yanfang Ye

International Conference on Machine Learning (ICML) 2025

[Paper] [Code]

Beyond Message Passing: Neural Graph Pattern Machine

Zehong Wang, Zheyuan Zhang, Tianyi Ma, Nitesh V Chawla, Chuxu Zhang, Yanfang Ye

International Conference on Machine Learning (ICML) 2025

[Paper] [Code]

Towards Graph Foundation Models: Learning Generalities Across Graphs via Task-Trees
Towards Graph Foundation Models: Learning Generalities Across Graphs via Task-Trees

Zehong Wang, Zheyuan Zhang, Tianyi Ma, Nitesh V Chawla, Chuxu Zhang, Yanfang Ye

International Conference on Machine Learning (ICML) 2025

[Paper] [Code]

Towards Graph Foundation Models: Learning Generalities Across Graphs via Task-Trees

Zehong Wang, Zheyuan Zhang, Tianyi Ma, Nitesh V Chawla, Chuxu Zhang, Yanfang Ye

International Conference on Machine Learning (ICML) 2025

[Paper] [Code]

Training MLPs on Graphs Without Supervision
Training MLPs on Graphs Without Supervision

Zehong Wang, Zheyuan Zhang, Chuxu Zhang, Yanfang Ye

ACM International Conference on Web Search and Data Mining (WSDM) 2025

[Paper] [Code]

Training MLPs on Graphs Without Supervision

Zehong Wang, Zheyuan Zhang, Chuxu Zhang, Yanfang Ye

ACM International Conference on Web Search and Data Mining (WSDM) 2025

[Paper] [Code]

Can LLMs Convert Graphs to Text-Attributed Graphs?
Can LLMs Convert Graphs to Text-Attributed Graphs?

Zehong Wang, Sidney Liu, Zheyuan Zhang, Tianyi Ma, Chuxu Zhang, Yanfang Ye

Conference of the Nations of the Americas Chapter of the Association for Computational Linguistics (NAACL) 2025

[Paper] [Code]

Can LLMs Convert Graphs to Text-Attributed Graphs?

Zehong Wang, Sidney Liu, Zheyuan Zhang, Tianyi Ma, Chuxu Zhang, Yanfang Ye

Conference of the Nations of the Americas Chapter of the Association for Computational Linguistics (NAACL) 2025

[Paper] [Code]

GFT: Graph Foundation Model with Transferable Tree Vocabulary
GFT: Graph Foundation Model with Transferable Tree Vocabulary

Zehong Wang, Zheyuan Zhang, Nitesh Chawla, Chuxu Zhang, Yanfang Ye

Annual Conference on Neural Information Processing Systems (NeurIPS) 2024

[Paper] [Code]

GFT: Graph Foundation Model with Transferable Tree Vocabulary

Zehong Wang, Zheyuan Zhang, Nitesh Chawla, Chuxu Zhang, Yanfang Ye

Annual Conference on Neural Information Processing Systems (NeurIPS) 2024

[Paper] [Code]

Diet-ODIN: A Novel Framework for Opioid Misuse Detection with Interpretable Dietary Patterns
Diet-ODIN: A Novel Framework for Opioid Misuse Detection with Interpretable Dietary Patterns

Zheyuan Zhang*, Zehong Wang*, Shifu Hou, Evan Hall, Landon Bachman, Jasmine White, Vincent Galassi, Nitesh V Chawla, Chuxu Zhang, Yanfang Ye (* equal contribution)

ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD) 2024

[Paper] [Code]

Diet-ODIN: A Novel Framework for Opioid Misuse Detection with Interpretable Dietary Patterns

Zheyuan Zhang*, Zehong Wang*, Shifu Hou, Evan Hall, Landon Bachman, Jasmine White, Vincent Galassi, Nitesh V Chawla, Chuxu Zhang, Yanfang Ye (* equal contribution)

ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD) 2024

[Paper] [Code]

Heterogeneous Graph Contrastive Multi-View Learning
Heterogeneous Graph Contrastive Multi-View Learning

Zehong Wang, Qi Li, Donghua Yu, Xiaolong Han, Xiao-Zhi Gao, Shigen Shen

SIAM International Conference on Data Mining (SDM) 2023

[Paper] [Code]

Heterogeneous Graph Contrastive Multi-View Learning

Zehong Wang, Qi Li, Donghua Yu, Xiaolong Han, Xiao-Zhi Gao, Shigen Shen

SIAM International Conference on Data Mining (SDM) 2023

[Paper] [Code]

All publications
Education
  • University of Notre Dame
    University of Notre Dame
    Department of Computer Science and Engineering
    Ph.D. Student
    Aug. 2023 - present
Experience
  • Amazon
    Amazon
    Applied Scientist Intern (Part-Time)
    Sept. 2025 - Oct. 2025
  • Amazon
    Amazon
    Applied Scientist Intern
    May. 2025 - Aug. 2025
Services
  • Reviewer, NeurIPS
    2024, 2025
  • Reviewer, ICLR
    2024, 2025, 2026
  • Reviewer, ICML
    2024, 2025
  • Reviewer, KDD
    2025
  • Reviewer, ARR (ACL, EMNLP, NAACL)
    2025
  • Reviewer, AISTATS
    2025, 2026
  • Reviewer, AAAI
    2024, 2025, 2026
  • Reviewer, ICML
    2024, 2025
Honors & Awards
  • NSF Access Grant
    2025
  • NeurIPS Scholar Award
    2025
  • ICML Scholar Award
    2025
  • Notre Dame Graduate School Conference Presentation Grant
    2025
  • WSDM Student Travel Award
    2025
  • SDM Doctoral Forum Travel Award
    2024