Hello everyone, my name is Zhongjian Zhang. Currently, I am a third-year Ph.D. student from Beijing University of Posts and Telecommunications (BUPT), supervised by Prof. Chuan Shi. My research interests primary focus on large language models and trustworthy graph machine learning. Specifically, my current research is mainly about the development of graph foundation model.
If you have any questions regarding my work or are interested in collaborating with me, please feel free to contact me.
🔥News
2025.12
💼 I join the Hong Kong University of Science and Technology (Guangzhou) as a research intern, supervised by Prof. Jia Li.
2025.12
🎉 My research is supported by the CAS Youth Talent Training Program for PhD Students.
2025.10
🎉 I receive the National PhD Scholarship from the Ministry of Education of China.
2025.04
🎉 My research is supported by the BUPT Excellent PhD Students Foundation: CX20251005.
2024.12
🎉 Our paper Spattack is accepted to AAAI 2025.
2024.11
🎉 Our paper LLM4RGNN is accepted to KDD 2025.
2024.06
💼 I join China Telecommunications Corporation as a research intern.
2024.01
🎉 Our paper GraphPAR is accepted to WWW 2024.
📝Publications
FRiskGPT: A Generative Foundation Model for Financial Risk Detection
CCF-A
@inproceedings{DBLP:conf/www/ZhangZXSLMXWWCT26,
author = {Zhongjian Zhang and
Mengmei Zhang and
Dehua Xu and
Rongjun Shi and
Jianfeng Liu and
Fuli Meng and
Huajian Xu and
Xiao Wang and
Ruijia Wang and
Junze Chen and
Minwei Tang and
Chuan Shi},
editor = {Hakim Hacid and
Yoelle Maarek and
Francesco Bonchi and
Ido Guy and
Emine Yilmaz},
title = {FRiskGPT: {A} Generative Foundation Model for Financial Risk Detection},
booktitle = {Proceedings of the {ACM} Web Conference 2026, {WWW} 2026, Dubai, United
Arab Emirates, originally scheduled for April 13-17, 2026, rescheduled
for June 29 - July 3, 2026},
pages = {7733--7744},
publisher = {{ACM}},
year = {2026},
url = {https://doi.org/10.1145/3774904.3792832},
doi = {10.1145/3774904.3792832},
timestamp = {Thu, 21 May 2026 17:35:30 +0200},
biburl = {https://dblp.org/rec/conf/www/ZhangZXSLMXWWCT26.bib},
bibsource = {dblp computer science bibliography, https://dblp.org}
}
Toward Graph-Tokenizing Large Language Models with Reconstructive Graph Instruction Tuning
CCF-A
@inproceedings{DBLP:conf/www/ZhangWZTS26,
author = {Zhongjian Zhang and
Xiao Wang and
Mengmei Zhang and
Jiarui Tan and
Chuan Shi},
editor = {Hakim Hacid and
Yoelle Maarek and
Francesco Bonchi and
Ido Guy and
Emine Yilmaz},
title = {Toward Graph-Tokenizing Large Language Models with Reconstructive
Graph Instruction Tuning},
booktitle = {Proceedings of the {ACM} Web Conference 2026, {WWW} 2026, Dubai, United
Arab Emirates, originally scheduled for April 13-17, 2026, rescheduled
for June 29 - July 3, 2026},
pages = {430--441},
publisher = {{ACM}},
year = {2026},
url = {https://doi.org/10.1145/3774904.3792077},
doi = {10.1145/3774904.3792077},
timestamp = {Thu, 21 May 2026 17:35:20 +0200},
biburl = {https://dblp.org/rec/conf/www/ZhangWZTS26.bib},
bibsource = {dblp computer science bibliography, https://dblp.org}
}
Can Large Language Models Improve the Adversarial Robustness of Graph Neural Networks?
CCF-A
@inproceedings{DBLP:conf/kdd/Zhang0Z0Z0025,
author = {Zhongjian Zhang and
Xiao Wang and
Huichi Zhou and
Yue Yu and
Mengmei Zhang and
Cheng Yang and
Chuan Shi},
title = {Can Large Language Models Improve the Adversarial Robustness of Graph
Neural Networks?},
booktitle = {Proceedings of the 31st {ACM} {SIGKDD} Conference on Knowledge Discovery
and Data Mining, V.1, {KDD} 2025, Toronto, ON, Canada, August 3-7,
2025},
pages = {2008--2019},
publisher = {{ACM}},
year = {2025},
url = {https://doi.org/10.1145/3690624.3709256},
doi = {10.1145/3690624.3709256}
}
Rethinking Byzantine Robustness in Federated Recommendation from Sparse Aggregation Perspective
CCF-A
@inproceedings{DBLP:conf/aaai/ZhangZWL00025,
author = {Zhongjian Zhang and
Mengmei Zhang and
Xiao Wang and
Lingjuan Lyu and
Bo Yan and
Junping Du and
Chuan Shi},
title = {Rethinking Byzantine Robustness in Federated Recommendation from Sparse
Aggregation Perspective},
booktitle = {Thirty-Ninth {AAAI} Conference on Artificial Intelligence, {AAAI} 2025, Philadelphia, PA, USA, February 25 - March 4, 2025},
pages = {13331--13338},
publisher = {{AAAI} Press},
year = {2025},
url = {https://doi.org/10.1609/aaai.v39i12.33455},
doi = {10.1609/AAAI.V39I12.33455}
}
Endowing Pre-trained Graph Models with Provable Fairness
CCF-A
@inproceedings{DBLP:conf/www/ZhangZYYLS24,
author = {Zhongjian Zhang and
Mengmei Zhang and
Yue Yu and
Cheng Yang and
Jiawei Liu and
Chuan Shi},
title = {Endowing Pre-trained Graph Models with Provable Fairness},
booktitle = {Proceedings of the {ACM} on Web Conference 2024, {WWW} 2024, Singapore,
May 13-17, 2024},
pages = {1045--1056},
publisher = {{ACM}},
year = {2024},
url = {https://doi.org/10.1145/3589334.3645703},
doi = {10.1145/3589334.3645703}
}
Data-centric graph learning: A survey
JCR-Q1
@article{DBLP:journals/tbd/GuoBYLZLPS25,
author = {Yuxin Guo and
Deyu Bo and
Cheng Yang and
Zhiyuan Lu and
Zhongjian Zhang and
Jixi Liu and
Yufei Peng and
Chuan Shi},
title = {Data-Centric Graph Learning: {A} Survey},
journal = {{IEEE} Trans. Big Data},
volume = {11},
number = {1},
pages = {1--20},
year = {2025},
url = {https://doi.org/10.1109/TBDATA.2024.3489412},
doi = {10.1109/TBDATA.2024.3489412}
}
🎖Honors and Awards
1CAST PhD Support Program, Youth Talent Development Initiative2025
2National PhD Scholarship, Ministry of Education of China2025
3BUPT Excellent Ph.D. Students Foundation (CX20251005)2025
4Outstanding Graduate Student, Beijing University of Posts and Telecommunications2024
5First-class Scholarship, Beijing University of Posts and Telecommunications2023
6Outstanding Student of Shandong Province (Top 0.5%)2022
72nd Prize, 13th Lanqiao Cup National Finals, Java Software Development2022
82nd Prize, National Final of Shandong Data Innovation Competition (Team Leader)2021
91st Prize, Challenge Cup Shandong Province (Team Leader)2021
10Shandong Provincial Government Scholarship (Top 0.5%)2021
💬Talks
2025.01
Rethinking Byzantine Robustness in Federated Recommendation from Sparse Aggregation Perspective
2024.12
Can Large Language Models Improve the Adversarial Robustness of Graph Neural Networks?
💻Experiences
2024.06 - 2025.02
China Telecommunications Corporation
Shanghai, China
Research internFinancial Risk Service
MentorMengmei Zhang
2025.12 - Now
Hong Kong University of Science and Technology (Guangzhou)
Guangzhou, China
Research internGraph Foundation Model, Large Language Model
MentorJia Li
