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.
[Open Positions]
- Research Assistant/Intern: Positions available anytime.
- Master of Philosophy (M.Phil.): Fall 2026. (Admission decisions are made by the admission committee; admitted students or qualified applicants are encouraged to contact me in advance.)
- Ph.D.: Fall 2027. (Master students or Bachelor students with strong research experience are encouraged to contact me in advance.)
Candidates with strong backgrounds in data mining, machine learning, mathematics, or related fields are encouraged to email their CV and transcript to enyandai@hkust-gz.edu.cn, using the subject line "[RA/M.Phil./Ph.D. Application - Your Name]".
Research Directions at 
(Trust & Application AI Lab)
I have wide research interests in Trustworthy AI and Applications of AI in the real-world scenarios.
Recent Blogs
- [Video] Introduction about Unnoticeable Backdoor Attacks on Graph Neural Networks (WWW-2023)
- [Video] Introduction about robust structural noise-resistant GNN (WWW-2022)
- A Comprehensive Survey on Trustworthy Graph Neural Networks: Privacy, Robustness, Fairness, and Explainability
News
- 09/2025: Serve as an Area Chair for ICLR-2026
- 06/2025: We released Protap: A Benchmark for Protein Modeling on Realistic Downstream Applications [package]
- 06/2025: 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
- 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