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 a trustworthy AI systems. Currently, I focus on the graph anomaly detection, backdoor attack and defense on graphs neural network and large language model. Additionally, I explore related areas such as:

Graph representation learning/Graph foundation model

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

I feel excited to work with colleagues at Machine Learning & Applications (MaLA) Lab, we investigates novel machine learning techniques, with a research theme focused 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 on large language models, graph learning, or anomaly detection, feel free to contact me (hezheqiao[at]gmail.com, Linkedln, or WeChat ) if you have any plan or are looking for a collaborator.

Pin

Check out our survey on deep graph anomaly detection Deep Graph Anomaly Detection: A Survey and New Perspectives and its github repository

We just released a github repository which summarized A collection of papers on foundation model for anomaly detection (tabular data/time series/image/video/graph/text/log), and published algorithms.

News

[New!] 2025/3: One paper on multi-label recognition is accepted to ICME 2025 .

[New!] 2025/3: I am very honored to be a student volunteer for SMU Workshop on Advances of Generative Artificial Intelligence (GenAI), in parallel with ICLR 2025, April 27, 2025

[New!] 2025/3: We just released a github repository which summarized A collection of papers on foundation model for anomaly detection (tabular data/time series/image/video/graph/text/log), and published algorithms.

2025/2: I will be joining University of Illinois at Urbana-Champaign as a visiting student in May, 2025 !

2025/1: Invited as PC Member for KDD 2025

2024/12: Invited as PC Member for ICME 2025

2024/10: One paper on time series data imputation is accepted to BIBM 2024

2024/9: Check out our survey on deep graph anomaly detection Deep Graph Anomaly Detection: A Survey and New Perspectives and its github repository

2024/9: One paper on semi-supervised graph anomaly detection is accepted to NeurIPS 2024

2024/9: One survey paper on deep hate speech detection is accepted to JDSA

2024/8: Invited as PC Member for ICLR 2025

2024/8: One paper on crossing intent prediction is accepted to ICONIP 2024

2024/7: Honored to receive the SMU Presidential Doctoral Fellowship (2024)

2024/6: Invited as PC Member for NeurIPS 2024

2024/5: One paper on normality learning for time series anomaly detection is accepted to ECML PKDD 2024

2024/4: I am very honored to be a student volunteer for WebConf 2024 , see you in Sentosa, Singapore, May 13 to May 17, 2024.

2024/2: Our PerCom24 paper DiTMoS is featured as Mark Weiser Best Paper Award !

2024/1: Invited as PC Member for PAKDD 2024

2024/1: Excited to announce that my research has now reached 100 citations on Google Scholar!

2023/12: One paper on diverse Tiny model selection is accepted to PerCom 2024

2023/09: One paper on unsupervised graph anomaly detection is accepted to NeurIPS 2023

2023/08: One paper on AI in medicine is accepted by Journal of the American Medical Informatics Association : JAMIA

2023/01: I am very honored to be a student volunteer for WSDM 2023 , see you in SMU, Singapore, February 27 to March 3, 2023.

2023/01: Check out our survey paper about deep learning for hate speech detection

2022/07: I have been offered admission into SMU-SCIS PhD programme with a full scholarship. The academic term will start on 9 January 2023.

2022/06: I have finished my master and will join School of Computing and Information Systems @ SMU as Research Engineer.

2022/05: Two papers on Review-based recommendation system and Alzheimer's disease clinical scores prediction are accepted to IJCNN 2022.

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 Science 2022

First prize, Dean Scholarship of Chengdu Branch, Chinese Academy Science 2021

Outstanding Student of University of the Chinese Academy of Sciences 2020, 2021

Outstanding graduates, Outstanding Student of the Chengdu University of Technology 2016,2017,2018,2019

Hundred Excellent Academic Dissertations of the Chengdu University of Technology 2019

Background

2022-present: Ph.D. in Computer Science, Singapore Management University, Singapore

2019-2022: Master in Computer Science, University of the Chinese Academy of Sciences, China

2015-2019: Bachelor in Computer Science and Technology, Chengdu University of Technology, China

Professional Experiences

School of Computing and Information Systems, SMU, research engineer advised by [Prof. Guansong Pang] 2022-2023

Chongqing Key Laboratory of Big Data and Intelligent Computing, CIGIT, research student advised by [Prof. Mingsheng Shang], [Prof. Lin Chen] and [Prof. Fan Zhu] 2020-2022.

Institute of Mountain Hazards and Environment, CAS, research assistant advised by [Prof. Xiaopeng Leng] and [Prof. Shaojie Zhang] 2019-2020.

Services

Program Committee (Selected)

ICLR, NeurIPS, KDD

Journal Reviewer (Selected)

IEEE TKDE, IEEE TNNLS, IEEE TAI

Teaching Experience

CS425: Natural Language Communication, (Undergraduate), Singapore Management University, Tutor, Autumn 2024

Student Volunteers

WSDM2023, WebConf2024

Current Students Co-supervision/Collaboration

Yutong Chen: PhD at UCAS with Prof. Guansong Pang, 09/2023-, time series anomaly detection (ECML PKDDx1)

Guolei Zeng: PhD at Oxford with Prof. Guansong Pang, 06/2024-, graph anomaly detection

Guoguo Ai: PhD at NJUST with Prof. Guansong Pang, 11/2024-, graph representation learning

Ye Su: MS at UCAS with Assistant Prof. Lin Chen, 06/2024-, time series prediction (BIBMx1)

Former Students Co-supervision/Collaboration

Haifu Ye: MS at UCAS with Assistant Prof. Lin Chen, 03/2024-04/2025, video anomaly detection

Hongbin Liang: MS at UCAS with Assistant Prof. Lin Chen, 03/2024-07/2024, pedestrian crossing intent prediction (ICONIPx1)

Ruhui Zhang: PhD at CUPT with Assistant Prof. Lin Chen, 10/2024-01/2025, multi-label recognition (ICMEx1)