About me

I am a tenure-track assistant professor in the AI Thrust at the Hong Kong University of Science and Technology (Guangzhou). I recevied my Ph.D. degree from the Pennsylvania State University under the supervision of Dr. Suhang Wang. I obtained my Master of AI degree from Computer Science Department at KU Leuven. I received my Bachelor Degree from the University of Science and Technology of China.

[Ph.D. student and Research Assistant Positions available]

I am seeking highly self-motivated Ph.D. students and Research Assistants to join my team starting in Fall 2025. Candidates with solid backgrounds in data mining, machine learning, mathematics and other related fields are encouraged to apply. If interested, please email me (enyandai@hkust-gz.edu.cn) your CV and transcript, kindly using the subject line "[Ph.D./RA Application - your name]."

Research Directions at (Trust & Application AI Lab)

The overview of the research directions are listed following. More details can be referred in my research statement.

Summary of Prior Works

Fair Graph Neural Network (WSDM-21) Paper Code

Privacy Preserving FairGNN (TKDE) Paper

Sensitive Attribute Protection (TKDE) Paper
Membership Privacy Protection (KDD-23) Paper
Deep IP Protection (Preprint) Paper

Label Noise-Resistant GNN (KDD-21) Paper Code
Defend Structural Noise (WSDM-22) Paper Code
Unnoticeable Graph Backdoor (WWW-23) Paper Code

Trustworthy Graph Learning

Self-Explainable GNN (CIKM-21) Paper Code

A Comprehensive Survey of Trustworthy Graph Neural Networks: Privacy, Robustness, Fairness, and Explainability. Paper

Graph-Augmented AI for Social Good

Fake Health News Repository with Social Network Context (ICWMS-20) Paper Dataset

Graph-Augmented Anomaly Detection on Power Grids (ICLR-22) Paper Code

Recent Blogs

News

06/2026: We released Protap: A Benchmark for Protein Modeling on Realistic Downstream Applications [package]
06/2026: Very honored that the paper LiSA: Leveraging Link Recommender to Attack Graph Neural Networks via Subgraph Injection corresponded by me received the PAKDD 2025 Best Paper Award!
05/2025: Two papers accepted by KDD-2025
- PreGIP: Watermarking the Pretraining of Graph Neural Networks for Deep Intellectual Property Protection
- Are You Using Reliable Graph Prompts? Trojan Prompt Attacks on Graph Neural Networks
1/2025: One paper entitled: Robustness Inspired Graph Backdoor Defense accepted by ICLR-2025 (Oral Paper)
11/2024: One paper entitled: Stealing Training Graphs from Graph Neural Networks accepted by KDD-2025
07/2024: One paper entitled: Towards Prototype-Based Self-Explainable Graph Neural Network accepted by TKDD
07/2024: Two papers accepted by CIKM-2024 in full paper track and short paper track respectively.
07/2024: I joined the AI Thrust at Hong Kong University of Science and Technology (Guangzhou).
05/2024: One paper entitled:Improving Issue-PR Link Prediction via Knowledge-aware Heterogeneous Graph Learning accepted by IEEE Transactions on Software Engineering
05/2024: One paper entitled: Rethinking Graph Backdoor Attacks: A Distribution-Preserving Perspective accepted by KDD-2024
09/2023: One paper entitiled: “Certifiably Robust Graph Contrastive Learning” accepted by NeurIPS-2023
09/2023: One paper entitled:”Learning Fair Models without Sensitive Attributes: A Generative Approach” accepted by Neurocomputing
05/2023: One paper entitled:”A Unified Framework of Graph Information Bottleneck for Robustness and Membership Privacy” accepted by KDD-2023
04/2023: Serve as reviewer of KDD-2023 and ICML-2023.
03/2023: Very glad to receive the IST Ph.D. Student Award for Research Excellence
01/2023: One paper entitled: “Unnoticeable Backdoor Attacks on Graph Neural Networks” has been accepted by WWW-2023
11/2022: One paper entitled: “Label-Wise Graph Convolutional Network for Heterophilic Graphs” has been accepted by LOG-2022
08/2022: One paper has been accepted by ICDM-2022
07/2022: One paper entitled: “Learning Fair Graph Neural Networks with Limited andPrivate Sensitive Attribute Information” has been accepted by TKDE
07/2022: Update a package of Robust GNN for Label Noises [code]
06/2022: Serve as a reviewer for NeurIPS-2022
06/2022: Serve as a PC memeber for ASONAM-2022
06/2022: Invited as a guest for Trustworthy Graph Learning Tutorial in DataFun
04/2022: Release a survey entitled: “A Comprehensive Survey on Trustworthy Graph Neural Networks: Privacy, Robustness, Fairness, and Explainability”
03/2022: Serve as a PC memeber for KDD-2022
01/2022: One paper entitled “Graph-Augmented Normalizing Flows for Anomaly Detection of Multiple Time Series” is accepted as Spotlight in ICLR-2022
10/2021: Two papers are accepted by WSDM-2022
08/2021: One paper is accepted by CIKM-2021
06/2021: Serve as a PC memeber for ASONAM-2021
05/2021: Two papers are accepted by KDD-2021
10/2020: One paper is accepted by WSDM-2021

Enyan Dai