Assistant Professor
Lee Kong Chian Fellow (2024-2026)
School of Computing and Information Systems
Singapore Management University
Room 5035, 80 Stamford Rd, Singapore 178902
Email: gspang[at]smu.edu.sg; pangguansong[at]gmail.com
Phone: +65-68264864
[LinkedIn] [X] [GitHub] [Google Scholar] [ORCID] [Top2%Scientists]
Guansong Pang is a tenure-track Assistant Professor of Computer Science and a Lee Kong Chian Fellow at the School of Computing and Information Systems, Singapore Management University (SMU). He is also a faculty member of Centre on Security, Mobile Applications and Cryptography. He was a Research Fellow with the Australian Institute for Machine Learning (AIML), University of Adelaide, Australia. Before joining AIML, he received his Ph.D. at University of Technology Sydney (UTS), Australia.
He leads the Machine Learning & Applications (MaLA) Lab at SMU. His research interests include machine learning, data mining, and computer vision, with a research theme focused on recognizing and generalizing to abnormal, unknown, or unseen data for building trustworthy AI systems in open environments. Research areas of particular interest include:
Anomaly detection
Open-world machine learning (e.g., out-of-distribution detection, open-set recognition, long-tailed classification, continual learning)
Specialized foundation models for specific type of data (e.g., graphs, time series, tabular) or tasks (e.g., anomaly detection, forecasting)
Security and safety in foundation models (hallucination mitigation, AI-generated content detection, defense against model/data attacks)
He also explores some pivotal real-world applications of these areas, such as network intrusion detection, fraud detection, early detection of diseases/faults, learning from biomedicine data, industrial defect detection, biometric anti-spoofing, and hate speech detection.
His research has received multiple prestigious recognition/awards, e.g., the 2020 UTS Chancellor's Award List, the World's Top 2% Scientists in 2022-2024, DSAA 2023 Best Paper Award (Applications Track), the Most Influential KDD 2023 Paper, and the Lee Kong Chian Fellowship award 2024.
He actively engages in various professional activities, serving as Area Chair of NeurIPS, ICLR, ICML, CVPR, KDD, PAKDD, IJCAI and AAAI, Associate Editor of IEEE Transactions on Neural Networks and Learning Systems and Pattern Recognition, and Editorial Board member of IEEE Intelligent Systems and International Journal of Data Science and Analytics.
Actively looking for candidates of the following positions; feel free to get in touch if you are interested (only shortlisted candidates will be contacted):
Highly motivated PhD students with strong research experience and background in computer science (scholarships).
Visiting professors/students.
Self-motivated students for remote research intern.
📢 Full scholarship for new PhD students.
📢 Full-time research engineers and grant-funded visiting PhD students, working on LLMs and multimodal LLMs for visual/sequence data
SMU is ranked top 30 in AI and top 80 in CS according to CSRankings.
My team and I will be part of the following events. You're most welcome to join and contribute.
Tutorial on "Foundation Models in Visual Anomaly Detection: Advances, Challenges, and Applications" at ICCV 2025, full morning of October 19, 2025, Hawai'i
Keynote at Workshop on AI for Financial Fraud Detection & Prevention, in conjunction with ACM Int. Conf. on AI in Finance 2025, November 15-16, 2025, Singapore
Tutorial on "Robust Graph Learning in Finance" at ACM Int. Conf. on AI in Finance 2025 , collaborating with colleagues from Institute of Computing Technology, Chinese Academy of Sciences, November 15-16, 2025, Singapore
Tutorial on "Toward Foundation Models for Detecting Abnormal Activities on Graphs" at AAAI 2026, full afternoon of January 21, 2026, Singapore
Keynote at AAAI 2026 Workshop on Automated Spatial and Temporal Anomaly Detection (ASTAD), January 26, 2026, Singapore
Keynote at AAAI 2026 Workshop on Agentic AI in Financial Services, January 26, 2026, Singapore
Special Issue on "Foundation Models for Anomaly Detection, Reasoning, and Recovery" in Pattern Recognition journal. Submission deadline: July 30, 2026
[10/2025] Invited to give keynote talks at AAAI 2026 workshops on Automated Spatial and Temporal Anomaly Detection (ASTAD) and Agentic AI in Financial Services
[09/2025] Our Pattern Recognition special issue on "Foundation Models for Anomaly Detection, Reasoning, and Recovery" starts to accept submission until July 30, 2026
[09/2025] Honored to be named in the list of The World's Top 2% Scientists 2025 in both career-long and single-year categories (first time named in the career-long category; rank is 26K in 2024 and lifted to 13K this year, subfield rank is 645 out of 458,615 authors).
[09/2025] Invited to give a keynote talk ACM ICAIF 2025 workshop on AI for Financial Fraud Detection & Prevention, November 15-16, 2025
[09/2025] Three papers on graph anomaly detection, LLM hallucinations, time series foundation models are accepted to NeurIPS 2025
[09/2025] One tutorial on graph anomaly detection is accepted to AAAI 2026
[09/2025] One tutorial on financial graph learning is accepted to ICAIF 2025
[08/2025] One paper on few-shot anomaly detection is accepted to CIKM 2025
[07/2025] One paper on joint class-incremental learning and OOD detection is accepted to Pattern Recognition
[07/2025] Congratulations to Jiawen and Hezhe for receiving both the 2025 SMU SCIS Dean's List and the 2025 SMU Presidential Doctoral Fellowship awards for their significant PhD research achievements
[06/2025] Two papers on VLM-enabled anomaly and out-of-distribution detection are accepted to ICCV 2025
[06/2025] One survey paper on deep graph anomaly detection is accepted to TKDE
[05/2025] Two papers on foundation models for graph anomaly detection are accepted to KDD 2025
[05/2025] Two papers on graph transformers and spatial-temporal forecasting are accepted to ICML 2025
[04/2025] Two papers on zero-shot graph anomaly detection and LLM-driven time series forecasting are accepted to IJCAI 2025
[04/2025] One tutorial proposal on foundation models in visual anomaly detection is accepted to ICCV 2025
[04/2025] One tutorial proposal on deep graph anomaly detection is accepted to IJCAI 2025
[04/2025] One paper on open-world object detection is accepted to TNNLS
[03/2025] Honored to give a keynote talk at WACV 2025 Workshop on Automated Spatial and Temporal Anomaly Detection (ASTAD@WACV 2025)
[02/2025] One paper on image enhancement is accepted to CVPR 2025
[02/2025] One paper on graph anomaly detection is accepted to TKDD
[02/2025] One paper on LLM-driven log anomaly detection is accepted to PAKDD 2025
[02/2025] One paper on continual learning of multimodal LLMs is accepted to TNNLS
[01/2025] One paper on open-set graph anomaly detection is accepted to ICLR 2025
[11/2024] One paper on image anomaly detection with data contamination is accepted to WACV 2025
[09/2024] Three papers on graph anomaly detection, OOD detection, and graph continual learning are accepted to NeurIPS 2024
[09/2024] Honored to be named in the list of The World's Top 2% Scientists 2024 in the single year category (lifting from a rank of ~84K in 2023 to ~26K this year)
[08/2024] Congratulations to Jiawen and Hezhe for receiving the 2024 SMU Presidential Doctoral Fellowship award
[08/2024] One paper on graph data augmentation is accepted to Neural Networks
[08/2024] Honored to give a keynote talk at IJCAI 2024 Workshop on Anomaly Detection with Foundation Models (ADFM@IJCAI 2024)
[07/2024] Two papers on detection of video anomalies and OODs are accepted to ACM Multimedia 2024
[07/2024] One paper on graph continual learning is accepted to ECAI 2024
[07/2024] Honored to receive the Lee Kong Chian Fellowship award for research excellence
[06/2024] One paper on predicting bacterial toxins is accepted to Bioinformatics
[05/2024] One paper on time series anomaly detection is accepted to ECMLPKDD 2024
[05/2024] One paper on cluster-wide malfunction detection is accepted to KDD 2024
[04/2024] One paper on time series anomaly detection is accepted to TKDE
[04/2024] Our survey paper on self-supervised learning for time series data is accepted to TPAMI
[03/2024] One paper on time series anomaly detection is accepted to ICDE 2024
[02/2024] Four papers on open-set, open-vocabulary, and generalist AD, and negative prompts for OOD detection are accepted to CVPR 2024
[01/2024] One paper on time series anomaly detection is accepted to Web Conference 2024
[01/2024] One paper on foundation model-enabled zero-shot anomaly detection is accepted to ICLR 2024
[01/2024] One paper on zero-shot recognition in open worlds is accepted to Pattern Recognition
[01/2024] Our workshop "Visual Anomaly and Novelty Detection (VAND)" is accepted to CVPR 2024. Stay tuned!