📖 Biography

I am a Ph.D. candidate at Singapore Management University, supervised by Prof. Guansong Pang. I also closely collaborate with Prof. Hanghang Tong. My research interests lie in using deep learning and machine learning to build trustworthy AI systems. Currently, I focus on graph anomaly detection, graph foundation model , and LLM Hallucination Detection and Mitigation. Besides, I also explore related areas such as:

• 🔗 Graph representation learning
• 🚨 Anomaly/Outlier detection (time series, image, video, tabular data)
• 🧠 LLM-based explanation for anomaly detection
• 🔒 Safety and security in foundation models
• 📰 Fake news, image and misinformation detection / Fact-checking /Video Defake

I’m excited to work with colleagues at the Machine Learning & Applications (MaLA) Lab, focusing on abnormal/unknown data instance detection and generalized learning algorithms for creating trustworthy continual AI systems.

Collaboration Opportunities

• I am always open to collaborations with researchers, as well as undergraduate and graduate students seeking Ph.D. positions in large language models, graph learning, or anomaly detection. Feel free to contact me via hezheqiao[at]gmail.com, LinkedIn, or WeChat.

Pin

• 🌐 Our tutorial Deep Learning for Graph Anomaly Detection is accepted to IJCAI 2025.
• 📄 Check out our survey on deep graph anomaly detection: Deep Graph Anomaly Detection: A Survey and New Perspectives and its GitHub repository.
• 📚 We released a GitHub repository summarizing papers on foundation models for anomaly detection: Awesome Anomaly Detection with Foundation Models.

News

• [New!] 2025/05: The website of coming IJCAI 2025 tutorial Deep Learning for Graph Anomaly Detection is released ! See you in Montreal, Canada!
• 2025/05: One paper on graph foundation model for GAD is accepted to KDD 2025.
• 2025/05: One paper on graph transformer is accepted to ICML 2025.
• 2025/04: Our tutorial Deep Learning for Graph Anomaly Detection is accepted to IJCAI 2025.
• 2025/04: One paper on zero-shot graph anomaly detection is accepted to IJCAI 2025.
• 2025/04: One paper on tiny-model selection is accepted to TMC.
• 2025/03: One paper on multi-label recognition is accepted to ICME 2025 Oral (15% of all submissions)).
• 2025/03: Honored to be a student volunteer for GenAI Workshop at ICLR 2025.
• 2025/02: I will join UIUC iDEA-iSAIL Joint Laboratory as a visiting student in May 2025!
• 2024/10: One paper on time series data imputation accepted to BIBM 2024.
• 2024/09: Survey on deep graph anomaly detection released on arXiv and GitHub.
• 2024/09: One paper on semi-supervised graph anomaly detection accepted to NeurIPS 2024.
• 2024/07: Honored to receive the SMU Presidential Doctoral Fellowship (2024).
• 2024/05: One paper on normality learning for time series anomaly detection accepted to ECML PKDD 2024.
• 2024/04: Honored to be student volunteer at WebConf 2024, Sentosa, Singapore.
• 2024/02: Our PerCom24 paper "DiTMoS" won the Mark Weiser Best Paper Award!
• 2023/12: One paper on diverse tiny model selection accepted to PerCom 2024.
• 2023/09: One paper on unsupervised graph anomaly detection accepted to NeurIPS 2023.
• 2023/01: Honored to be student volunteer at WSDM 2023, SMU, Singapore.
• 2023/01: Survey paper on deep learning for hate speech detection released on arXiv and GitHub.
• 2022/07: Admitted to SMU-SCIS Ph.D. program with full scholarship, starting January 2023.
• 2022/06: Completed Master's degree and joined SMU SCIS as a Research Engineer.

Honors and Awards

• SMU Presidential Doctoral Fellowship, 2024
• Mark Weiser Best Paper Award, PerCom 2023
• PhD Full Scholarship, Ministry of Education, Singapore, 2023
• Dean Scholarship, Chinese Academy of Sciences, 2022
• First Prize, Dean Scholarship, Chengdu Branch, CAS, 2021

Services

• Program Committee (Selected): ICLR, NeurIPS, KDD
• Journal Reviewer (Selected): IEEE TKDE, IEEE TNNLS
• Teaching Experience: CS425 - Natural Language Communication (Undergraduate), Tutor, Autumn 2024, SMU
• Student Volunteer: WSDM 2023, WebConf 2024