Hezhe Qiao's Website

PhD Student
School of Computing and Information Systems
Singapore Management University

Email:
hezheqiao.2022[at]phdcs.smu.edu.sg
hezheqiao[at]gmail.com

• Google Scholar • GitHub • Twitter • LinkedIn

Office:
SMU School of Computing and Information Systems, Singapore 178902

📖 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 LLM/VLLM hallucination detection and mitigation, graph anomaly detection, and foundation model for anomaly detection. Besides, I also explore the following area

🔗 Graph representation learning
🚨 Anomaly/Outlier detection (time series, image, video, tabular data)
🧠 Specialized foundation models for specific type of data
🔒 Safety and security in foundation models
📰 Fake news, image and misinformation detection / Fact-checking

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.

2026 Summer Internship Searching

I am expected to graduate in December 2026 and am actively seeking industry internship in Singapore on LLM related topics. Feel free to contact me via hezheqiao[at]gmail.com, LinkedIn, or WeChat if you have any recommendation.

🧩Our tutorial Toward Foundation Models for Detecting Abnormal Activities on Graphs is accepted in AAAI 2026.
🌐 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.
🤖 You're welcome to star ⭐ and follow the GitHub repository on LLM hallucination evaluation benchmark, detection and mitigation: Awesome LLM Hallucination Detection and Mitigation.

News

[New!] 2025/10: One paper on graph representation learning is accepted to TKDE.
2025/09: The website of upcoming AAAI 2026 tutorial Toward Foundation Models for Detecting Abnormal Activities on Graphs is released! See you in Singapore!
2025/09: One paper on semi-supervised graph anomaly detection is accepted to NeurIPS 2025.
2025/09: Our tutorial Toward Foundation Models for Detecting Abnormal Activities on Graphs is accepted in AAAI 2026.
2025/08: Our tutorial Robust Graph Learning in Finance is accepted in ICAIF 2025.
2025/08: The slides of IJCAI 2025 tutorial Deep Learning for Graph Anomaly Detection are released.
2025/08: Honored to be a student volunteer for KDD 2025 and IJCAI 2025.
2025/07: Honored to receive the SMU SCIS Dean's List and SMU Presidential Doctoral Fellowship.
2025/06: One survey paper on deep graph anomaly detection is accepted to TKDE.
2025/05: The website of upcoming 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 SCIS Dean's List, 2025
SMU Presidential Doctoral Fellowship, 2024, 2025
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

Experience

🌍 2025/5 - 2025/11 : Visiting PhD student at University of Illinois Urbana-Champaign (UIUC) (Advisor: Prof. Hanghang Tong)

Services