Jianpeng Chen

About Me

I am currently a Ph.D. student in the Department of Computer Science at Virginia Tech since Aug. 2023, where I am advised by Prof. Dawei Zhou in VLOG Lab. My current concentration is multi-modal/view/graph challenges in AI for Science, especially metamaterial discovery, material/molecular modeling and simulation, etc.

Generally, my research lies in data mining and machine learning, with a particular focus on graph learning and self-supervised multi-modal/view/graph learning. Furthermore, I seek to apply my research to scientific domains such as 3D graph modeling of metamaterials and molecules, etc., contributing to the community of AI for science. I aim to provide novel insights into these areas, and some major results are as follows.

Metamaterial Discovery (KDD DB’25) provides the first benchmark for metamaterial that integrates heterogeneous data, ML models, novel metrics, and a visual-interactive interface.
3D Molecule Learning (IJCAI Demo’24) explores the effectiveness of functional groups for molecular tasks (molecular property prediction, conformation generation, etc.).
Heterophilous Multi-View Graph Learning (AAAI’23, AAAI’24, preprint’24) focuses on heterophily issues of graph learning, exploring how to utilize and exempt heterophilous information within multi-view graphs.
Multi-View Graph Learning (TNNLS’25, ICONIP’22) first studies complex graph-structured data under a multi-view scenario, providing different insights of collaborations between graphs for self-supervised learning.
Graph Semantic Extraction (INS’24) dives into extracting task-relevant semantic information from graphs.

Research Interests

Data Mining: Graph learning, Multi-modal/view/graph learning, Geometric generation
AI for Science: Metamaterial discovery, Molecular dynamic simulation

News

[Aug. 2025] My research topic on Metamaterial discovery is accepted by ICDM PhD Forum. See you in DC.
[June 2025] I am pleased to receive the Virginia Tech Travel Award from the Department of Computer Science at VT.
[May 2025] Our benchmark, MetamatBench, about Metamaterial Discovery is accepted by KDD Datasets and Benchmarks Track 2025. See you in Toronto.
[April 2025] Our paper Unimate about Metamaterial Discovery is accepted by ICML 2025.
[Mar 2025] I will give a Talk about Metamaterial on Towards Agentic AI for Science at AAAI Spring Symposia 2025. See you in SF.
[Mar 2025] Our demo MetaScientist about Metamaterial Scientist is accepted by NAACL 2025.
[Jan. 2025] Our paper VGMGC about Multi-view Clustering and Graph Geneartion is accepted by TNNLS.

Selected Publications

(Refer to Google Scholar for full publication list.)

KDD DB

MetamatBench: Integrating Heterogeneous Data, Computational Tools, and Visual Interface for Metamaterial Discovery

Jianpeng Chen, Wangzhi Zhan, Haohui Wang, Zian Jia, Jingru Gan, Junkai Zhang, Jingyuan Qi, Tingwei Chen, Lifu Huang, Muhao Chen, Ling Li, Wei Wang, Dawei Zhou

Proceedings of the 31st ACM SIGKDD Conference on Knowledge Discovery and Data Mining DB Track(KDD DB), 2025

PDF Code Project Page BibTex

ICML

UniMate: A Unified Model for Mechanical Metamaterial Generation, Property Prediction, and Condition Confirmation

Wangzhi Zhan, Jianpeng Chen, Dongqi Fu, Dawei Zhou

Forty-second International Conference on Machine Learning (ICML), 2025

Code

NAACL Demo

MetaScientist: A Human-AI Synergistic Framework for Automated Mechanical Metamaterial Design

Jingyuan Qi, Zian Jia, Minqian Liu, Wangzhi Zhan, Junkai Zhang, Xiaofei Wen, Jingru Gan, Jianpeng Chen, Qin Liu, Mingyu Derek Ma, Bangzheng Li, Haohui Wang, Adithya Kulkarni, Muhao Chen, Dawei Zhou, Ling Li, Wei Wang, Lifu Huang

2025 Annual Conference of the North American Chapter of the Association for Computational Linguistics -- System Demonstration Track (NAACL Demo), 2025

PDF Project Page BibTex

TNNLS

Variational Graph Generator for Multi-View Graph Clustering

Jianpeng Chen, Yawen Ling, Jie Xu, Yazhou Ren*, Shudong Huang, Xiaorong Pu, Zhifeng Hao, S Yu Philip, Lifang He

IEEE Transactions on Neural Networks and Learning Systems (TNNLS)

PDF Code BibTex

NeurIPS DB

Towards Heterogeneous Long-tailed Learning: Benchmarking, Metrics, and Toolbox

Haohui Wang, Weijie Guan, Jianpeng Chen, Zi Wang, Dawei Zhou

Thirty-eighth Conference on Neural Information Processing Systems DB Track (NeurIPS DB), 2024

PDF

Arxiv

Similarity-Enhanced Homophily for Multi-View Heterophilous Graph Clustering

Jianpeng Chen, Yawen Ling (Equal Contribution), Yazhou Ren*, Zichen Wen, Tianyi Wu, Shufei Zhang, Lifang He (Equal Contribution)

Preprint

PDF

IJCAI Demo

3D-FuM: Benchmarking 3D Molecule Learning with Functional Groups

Tingwei Chen, Jianpeng Chen (Equal Contribution), Dawei Zhou

Proceedings of the 33rd International Joint Conference on Artificial Intelligence Demo Track (IJCAI Demo), 2024

PDF

AAAI

Dual Label-Guided Graph Refinement for Multi-View Graph Clustering

Yawen Ling, Jianpeng Chen (Equal Contribution), Yazhou Ren*, Xiaorong Pu, Jie Xu, Xiaofeng Zhu, Lifang He

Proceedings of the 37th AAAI Conference on Artificial Intelligence (AAAI), 2023

PDF Code Oral Presentation

ICONIP

Shared-Attribute Multi-Graph Clustering with Global Self-Attention

Jianpeng Chen, Zhimeng Yang, Xiaorong Pu, Yazhou Ren*, Li Gao, Lifang He

Proceedings of the 29th International Conference on Neural Information Processing (ICONIP), 2022

PDF Code BibTex LNCS AC=14.6%, Oral Presentation

INS

Customizing Graph Neural Network using Path Reweighting

Jianpeng Chen, Yujing Wang (Equal Contribution), Ming Zeng (Equal Contribution), Zongyi Xiang, Bitan Hou, Yunhai Tong, Ole J Mengshoel, Yazhou Ren*

Information Sciences

PDF Code

Talks

Accepted Talk (Integrating Heterogeneous Data, Computational Tools, and Visual Interface for Metamaterial Discovery) at Towards Agentic AI for Science, AAAI Spring Symposia 2025

About Me

Research Interests

News

Selected Publications

Talks

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