Research Interests

My research broadly lies in Natural Language Processing and Machine Learning. Specifically, I focus on applying Multi-Modal and Retrieval-Augmented Large Language Models to the following real-world problems:

• Fact-Checking: Multi-Modal, Retrieval-Augmented, and Explainable Fact-Checking; Claim and Argument Detection.

• Question Answering: Multi-Modal Question Answering; Retrieval-Augmented Question Answering.

• Recommender Systems: Multi-Modal Recommender Systems; Graph-Enhanced Recommender Systems.

• AI for Science: AI for Protein, Molecule, Healthcare, and Research.

Work Experience

• University of Sheffield, UK, 2025 - Present

Assistant Professor (UK Lecturer)

• The Pennsylvania State University, USA, 2024 - 2025

Postdoctoral Researcher

• Yale University, USA, 2023 - 2024

Postdoctoral Researcher

Education

• Singapore Management University, Singapore, 2018 - 2023

PhD in Computer Science

• Sichuan University, P. R. China, 2014 - 2018

BEng in Computer Science (Outstanding Graduate Award)

BEcon in Financial Engineering (Outstanding Graduate Award)

Publications

1. Does Multimodal Large Language Model Truly Unlearn? Stealthy MLLM Unlearning Attack,

Xianren Zhang, Hui Liu, Delvin Ce Zhang, Xianfeng Tang, Qi He, Dongwon Lee, and Suhang Wang,

The 2025 Conference on Empirical Methods in Natural Language Processing (EMNLP-25), Nov 2025.

2. Unmasking Fake Careers: Detecting Machine-Generated Career Trajectories via Multi-Layer Heterogeneous Graphs,

Michiharu Yamashita, Thanh Tran, Delvin Ce Zhang, and Dongwon Lee,

The 2025 Conference on Empirical Methods in Natural Language Processing (EMNLP-25), Nov 2025.

3. Retrieval-Augmented Language Model for Knowledge-Aware Protein Encoding,

Jiasheng Zhang, Delvin Ce Zhang, Shuang Liang, Zhengpin Li, Rex Ying, and Jie Shao,

The 42nd International Conference on Machine Learning (ICML-25), Jul 2025.

4. Enhancing News Recommendation with Hierarchical LLM Prompting,

Dang Hai Kieu, Delvin Ce Zhang, Minh Duc Nguyen, Min Xu, Qiang Wu, and Dung D. Le,

The ACM Web Conference 2025 (WWW-25), Emerging World Track, Apr 2025.

5. CORRECT: Context- and Reference-Augmented Reasoning and Prompting for Fact-Checking,

Delvin Ce Zhang and Dongwon Lee,

2025 Annual Conference of the Nations of the Americas Chapter of the Association for Computational Linguistics (NAACL-25), Apr 2025. (code)

6. FASTopic: Pretrained Transformer is a Fast, Adaptive, Stable, and Transferable Topic Model,

Xiaobao Wu, Thong Nguyen, Delvin Ce Zhang, William Yang Wang, and Anh Tuan Luu,

The 38th Conference on Neural Information Processing Systems (NeurIPS-24), Dec 2024. (code)

7. Hypformer: Exploring Efficient Transformer Fully in Hyperbolic Space,

Menglin Yang, Harshit Verma, Delvin Ce Zhang, Jiahong Liu, Irwin King, and Rex Ying,

The 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD-24), Aug 2024. (code)

8. Topic Modeling on Document Networks with Dirichlet Optimal Transport Barycenter (Extended Abstract),

Delvin Ce Zhang and Hady W. Lauw,

The 40th IEEE International Conference on Data Engineering (ICDE-24), May 2024. (code)

9. Topic Modeling on Document Networks with Dirichlet Optimal Transport Barycenter,

Delvin Ce Zhang and Hady W. Lauw,

IEEE Transactions on Knowledge and Data Engineering (TKDE-24), vol. 36, no. 3, pp. 1328-1340, Mar 2024. (code)

10. Hyperbolic Graph Topic Modeling Network with Continuously Updated Topic Tree,

Delvin Ce Zhang, Rex Ying, and Hady W. Lauw,

The 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD-23), Aug 2023. (code)

Best Oral Talk Award Runner-Up, Singapore ACM SIGKDD Symposium 2023, Jul 2023. (certificate)

11. Meta-Complementing the Semantics of Short Texts in Neural Topic Models,

Delvin Ce Zhang and Hady W. Lauw,

The 36th Conference on Neural Information Processing Systems (NeurIPS-22), Dec 2022.

12. Variational Graph Author Topic Modeling,

Delvin Ce Zhang and Hady W. Lauw,

The 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD-22), Aug 2022. (code)

13. Dynamic Topic Models for Temporal Document Networks,

Delvin Ce Zhang and Hady W. Lauw,

The 39th International Conference on Machine Learning (ICML-22), Jul 2022.

Selected as Spotlight presentation on ICML-22.

14. Topic Modeling for Multi-Aspect Listwise Comparisons,

Delvin Ce Zhang and Hady W. Lauw,

The 30th ACM International Conference on Information and Knowledge Management (CIKM-21), Nov 2021. (code)

15. Representation Learning on Multi-Layered Heterogeneous Network,

Delvin Ce Zhang and Hady W. Lauw,

European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML/PKDD-21), Sep 2021.

16. Semi-Supervised Semantic Visualization for Networked Documents,

Delvin Ce Zhang and Hady W. Lauw,

European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML/PKDD-21), Sep 2021. (code)

17. Topic Modeling on Document Networks with Adjacent-Encoder,

Ce Zhang and Hady W. Lauw,

The 34th AAAI Conference on Artificial Intelligence (AAAI-20), Feb 2020. (code)

Preprints

1. Hierarchical Graph Topic Modeling with Topic Tree-based Transformer,

Delvin Ce Zhang, Menglin Yang, Xiaobao Wu, Jiasheng Zhang, and Hady W. Lauw.

Tutorial Delivery

1. Text-Attributed Graph Representation Learning: Methods, Applications, and Challenges,

Delvin Ce Zhang, Menglin Yang, Rex Ying, and Hady W. Lauw,

The ACM Web Conference 2024 (WWW-24), May 2024. (slides) (video, the highest viewed video among all 20 tutorials on WWW-24)

Research Grants

• Co-PI, USA NSF NAIRR Pilot Grant: Multi-Modal Scientific Claim Verification, 2024 - 2025

Conference Organization

• Technical Chair, The 12th IEEE International Conference on Data Science and Advanced Analytics (DSAA-25), Oct 2025.

Conference Program Committee Member

• 2026: AAAI, WSDM

• 2025: NeurIPS, ICML, ICLR, ACML, IJCAI, AISTATS, KDD, WWW, SIGIR, CIKM

• 2024: NeurIPS, ICML, ICLR, IJCAI, KDD, WWW, CIKM, SDM, LOG

• 2023: NeurIPS, ICML, IJCAI, KDD, WWW, LOG, NeurIPS GLFrontiers Workshop (Area Chair)

• 2022: NeurIPS, ICML, KDD, WWW, ACL, LOG

Journal Reviewer

• IEEE Transactions on Computational Social Systems (TCSS)

• IEEE Transactions on Intelligent Transportation Systems (TITS)

• IEEE Transactions on Knowledge and Data Engineering (TKDE)

• Information Processing and Management (IPM)

• Frontiers of Computer Science (FCS)

Teaching

• Instructor, COM1002 Foundations of Computer Science, University of Sheffield, AY2025/26 Term 2.

  • This course is taught in two terms. Course materials cover discrete mathematics, calculus, linear algebra, etc.

• Instructor, IS1702 Computational Thinking, Singapore Management University, AY2022/23 Term 2.

  • Course materials cover data structures, complexity analysis, algorithm design, etc.

  • Check teaching video recordings here.

Awards

• Best Oral Talk Award Runner-Up, Singapore ACM SIGKDD Symposium 2023, 2023.

• Dean's List (top 10%), School of Computing and Information Systems, Singapore Management University, 2022.

• Presidential Doctoral Fellowship 2022 (top 15%), Singapore Management University, 2022.

• Singapore Data Science Consortium (SDSC) PhD Dissertation Research Fellowship 2021 (only 6 PhD recipients across all Singapore universities in 2021), Singapore Data Science Consortium, 2021.

• Presidential Doctoral Fellowship 2020 (top 15%), Singapore Management University, 2020.

• Outstanding Graduate Award, Sichuan University, 2018.

• Computer Science Star (1/380+), Sichuan University, 2018.

• First-class Scholarship (top 2%), Sichuan University, 2014-2018.

• Outstanding Student Award, Outstanding Volunteer Award, Outstanding Student Union Member Award, Sichuan University, 2014-2018.