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 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/unseen data for learning trustworthy AI systems in open environments. Some research areas of particular interest include:
Anomaly detection
Open-world learning (out-of-distribution detection, open-set recognition, long-tailed classification, continual learning, open-vocabulary learning)
Deep learning and foundation models on graphs, time series, tabular data
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, and IJCAI, 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 professor/students.
Self-motivated students for remote research interns.
📢 Full scholarship or funding support for new PhD/research engineer/visiting students.
SMU is ranked top 50 in AI and top 80 in CS according to CSRankings.
CVPR 2025 Workshop on Visual Anomaly and Novelty Detection (VAND 3.0) Challenge is calling for participation, submission deadline: May 26, 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 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!
[12/2023] Three papers on video anomaly detection, OOD detection in long-tailed recognition, and open-vocabulary object detection are accepted to AAAI 2024
[11/2023] One paper on graph self-supervised learning is accepted to TNNLS
[10/2023] Our DSAA 2023 paper received the Best Paper Award of the Applications Track
[10/2023] Honored to be named in the list of The World's Top 2% Scientists 2023 in the single year category (a climb from a rank of ~270K in 2022 to ~84K this year)
[09/2023] One paper on graph anomaly detection is accepted to NeurIPS 2023
[07/2023] One paper on heterogeneous graph-level anomaly detection is accepted to DSAA 2023
[07/2023] Three papers on anomaly detection and OOD detection are accepted to ICCV 2023
[07/2023] One paper on semi-supervised anomaly detection is accepted to Information Processing & Management (IP&M).
[06/2023] Invited to be Publication Co-chair of IEEE CAI 2024 (IEEE Conference on AI)
[06/2023] One paper on medical image anomaly detection and segmentation is accepted to Medical Image Analysis (MedIA)
[06/2023] One paper on graph-level anomaly detection is accepted to ECML/PKDD 2023
[05/2023] One paper on weakly-supervised anomaly detection is accepted to KDD 2023
[05/2023] One tutorial on anomaly detection is accepted to IJCAI 2023
[04/2023] One paper on deep isolation forest is accepted to TKDE.
[04/2023] Our tutorial on "Revolutionizing Anomaly Detection: Approaches and Guidelines" is accepted to ECML/PKDD 2023
[02/2023] One paper on few-shot open-set recognition is accepted to CVPR 2023
[02/2023] Our tutorial on "Recent Advances in Anomaly Detection" is accepted to CVPR 2023