Research Interests

• Graph Representation Learning: Graph Neural Networks; Homogeneous, Heterogeneous, and Knowledge Graph Representation Learning; Recommender Systems.

• Text Mining: Large and Multi-modal Language Models; Text Classification; Text Retrieval; Neural Topic Modeling.

• AI for Protein and Health Science: Graph and LLM for Multi-modal Protein Representation Learning for Biomedical and Healthcare Tasks.

• Fact-Checking: Multi-modal and Explainable Fact-Checking.

Work Experience

• The Pennsylvania State University (PSU), USA, Apr 2024 - Present

Postdoctoral Researcher

• Yale University, USA, Sep 2023 - Mar 2024

Postdoctoral Researcher

• Singapore Management University (SMU), Singapore, Jan 2023 - May 2023

Instructor

Education

• Singapore Management University (SMU), Singapore, Aug 2018 - Jul 2023

PhD in Computer Science

• Sichuan University (SCU), P. R. China, Sep 2014 - Jun 2018

BEng in Computer Science (Outstanding Graduate Award)

BEcon in Financial Engineering (Outstanding Graduate Award)

Publications

1. FASTopic: A Fast, Adaptive, Stable, and Transferable Topic Modeling Paradigm,

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

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

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

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

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

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

Delvin Ce Zhang and Hady W. Lauw,

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

4. 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)

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

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

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)

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

Delvin Ce Zhang and Hady W. Lauw,

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

7. Variational Graph Author Topic Modeling,

Delvin Ce Zhang and Hady W. Lauw,

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

8. Dynamic Topic Models for Temporal Document Networks,

Delvin Ce Zhang and Hady W. Lauw,

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

9. Topic Modeling for Multi-Aspect Listwise Comparisons,

Delvin Ce Zhang and Hady W. Lauw,

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

10. 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.

11. 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)

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

Ce Zhang and Hady W. Lauw,

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

Tutorial Delivery

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

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

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

Conference Program Committee Member

• 2025: ICLR, KDD, WWW, AISTATS

• 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 Intelligent Transportation Systems (TITS)

• Information Processing and Management (IPM)

• Frontiers of Computer Science (FCS)

Teaching Experience

• Instructor, IS1702 Computational Thinking,

Singapore Management University, Spring 2023.

• • I independently taught an undergraduate compulsory course throughout the whole term. Course materials include data structures, complexity, algorithm design, etc.

  • Check teaching video recordings here.

• Teaching Assistant, IS1702 Computational Thinking,

Singapore Management University, Fall 2021.

• Teaching Assistant, IS786 Advanced Research Topics - Research Topics in Information Systems,

Singapore Management University, Spring 2021.

• Teaching Assistant, IS712 Machine Learning,

Singapore Management University, Fall 2020.

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.