Hello, welcome to Zizhou Wang's homepage!

I am a research scientist at the Institute of High Performance Computing (IHPC), Agency for Science, Technology and Research (A*STAR), Singapore. My research focuses on AI safety and robustness, with applications in healthcare and safety-critical domains. I have published papers in top-tier journals and conferences, including IEEE Transactions on Neural Networks and Learning Systems (TNNLS), IEEE Transactions on Cybernetics (TCyb), and IEEE Transactions on Medical Imaging (TMI).

Prior to joining A*STAR, I received my Ph.D. in Computer Science from Sichuan University, China, in 2022, under the supervision of Professor Lei Zhang. My research interests broadly span AI safety, robust AI, domain generalisation, and trustworthy AI for healthcare.

Contact: wang_zizhou@a-star.edu.sg

Recent Publications

2025

Single-Domain Generalization via Path Flatness-Aware Optimization of Loss Landscapes

Zizhou Wang, Wang, Y., Du, J., Feng, Y., Zhou, J.T., Goh, R.S.M., Liu, Y., Zhen, L.
IEEE Transactions on Neural Networks and Learning Systems, 2025

A Multi-Stage Multi-Modal Learning Algorithm with Adaptive Multimodal Fusion for Improving Multi-Label Skin Lesion Classification

Zuo, L., Zizhou Wang, Wang, Y.
Artificial Intelligence in Medicine, 2025

GAPNet: A Lightweight Framework for Image and Video Salient Object Detection via Granularity-Aware Paradigm

Wu, Y.-H., Liu, W., Zhu, Z.-X., Zizhou Wang, Liu, Y., Zhen, L.
Machine Intelligence Research (MIR), 2025

GapMatch: Bridging Instance and Model Perturbations for Enhanced Semi-Supervised Medical Image Segmentation

Huang, W., Zhang, L., Zizhou Wang, Wang, Y.
Proceedings of AAAI, 2025

Cross-Modal Obfuscation for Jailbreak Attacks on Large Vision-Language Models

Jiang, L., Zhang, Z., Zizhou Wang, Sun, X., Li, Z., Zhen, L., Xu, X.
arXiv preprint arXiv:2506.16760, 2025
2024

Geometric Correspondence-Based Multimodal Learning for Ophthalmic Image Analysis

Wang, Y., Zhen, L., … Zizhou Wang, et al.
IEEE Transactions on Medical Imaging, 2024

MedNAS: Multiscale Training-Free Neural Architecture Search for Medical Image Analysis

Wang, Y., Zhen, L., Zhang, J., Li, M., Zhang, L., Zizhou Wang, Feng, Y., Xue, Y., Wang, X., Chen, Z., Luo, T., Goh, R.S.M., Liu, Y.
IEEE Transactions on Evolutionary Computation, 2024

Continuous Disentangled Joint Space Learning for Domain Generalization

Zizhou Wang, Wang, Y., Feng, Y., Du, J., Liu, Y., Goh, R.S.M., Zhen, L.
IEEE Transactions on Neural Networks and Learning Systems, 2024

Adaptive Annotation Correlation Based Multi-Annotation Learning for Calibrated Medical Image Segmentation

Huang, W., Zhang, L., Shu, X., Zizhou Wang, Yi, Z.
IEEE Journal of Biomedical and Health Informatics, 2024

Exploring Inherent Consistency for Semi-Supervised Anatomical Structure Segmentation

Huang, W., Zhang, L., Shu, X., Wang, L., Zizhou Wang
IEEE Transactions on Medical Imaging, 2024
2023

Contrastive Domain Adaptation with Consistency Match for Automated Pneumonia Diagnosis

Feng, Y., Zizhou Wang, Xu, X., Wang, Y., Fu, H., Li, S., Zhen, L., Lei, X., Cui, Y., Ting, J.S.Z., et al.
Medical Image Analysis, 83, 102664, 2023

Learning Representation via Indirect Feature Decorrelation with Bi-Vector-Based Contrastive Learning for Clustering

Xie, X., Zhang, L., Wang, Y., Zizhou Wang, Hua, Y.
Information Sciences, 625, 141–156, 2023

Fine-Grained Recognition: Multi-Granularity Labels and Category Similarity Matrix

Shu, X., Zhang, L., Zizhou Wang, Wang, L., Yi, Z.
Knowledge-Based Systems, 273, 110599, 2023

Consistent Representation via Contrastive Learning for Skin Lesion Diagnosis

Zizhou Wang, Zhang, L., Shu, X., Wang, Y., Feng, Y.
Computer Methods and Programs in Biomedicine, 242, 107826, 2023

Performance Test of a Well-Trained Model for Meningioma Segmentation in Health Care Centers

Chen, C., Teng, Y., Tan, S., Zizhou Wang, Zhang, L., Xu, J.
JMIR, 25, e44119, 2023
2022

Uncertainty-Guided Voxel-Level Supervised Contrastive Learning for Semi-Supervised Medical Image Segmentation

Hua, Y., Shu, X., Zizhou Wang, Zhang, L.
International Journal of Neural Systems, 32(4), 2250016, 2022

Feature Pyramid Network with Level-Aware Attention for Meningioma Segmentation

Huang, W., Shu, X., Zizhou Wang, Zhang, L., Chen, C., Xu, J., Yi, Z.
IEEE Transactions on Emerging Topics in Computational Intelligence, 6(5), 1201–1210, 2022

Boundary-Aware Network with Topological Consistency Constraint for Optic Chiasm Segmentation

Huang, W., Shu, X., Zizhou Wang, Chen, C., Zhang, Y., Zhang, L., Xu, J.
IEEE Transactions on Artificial Intelligence, 4(6), 1504–1513, 2022

A Feature Space-Restricted Attention Attack on Medical Deep Learning Systems

Zizhou Wang, Shu, X., Wang, Y., Feng, Y., Zhang, L., Yi, Z.
IEEE Transactions on Cybernetics, 53(8), 5323–5335, 2022

Deep Slice-Crossed Network with Local Weighted Loss for Brain Metastases Segmentation

Shu, X., Zhang, L., Qu, J., Wang, L., Zizhou Wang, Zhang, W., Wang, Y., Lui, S.
IEEE Transactions on Cognitive and Developmental Systems, 15(3), 1419–1429, 2022

Patents & Technology Disclosures

Patent: Fast segmentation and characterization method for meningioma based on deep neural, China National Intellectual Property Administration, No. CN202110161083.2
Patent: A neural network-based method for automatic segmentation of optic nerve and measurement of compression, China National Intellectual Property Administration, No. CN202111310100.0
Patent: An automatic method for outlining cerebral arteries based on deep neural, China National Intellectual Property Administration, No. CN202111310166.X
Technology Disclosure: A Deep Learning-Based Method for Self-Monitoring of Atopic Dermatitis Using Smartphones, No. IHPC-TD-CI-2024-037
Technology Disclosure: AI-powered Skin Ageing Monitoring and Management via Mobile Devices, No. IHPC-TD-CI-2024-072

Awards & Honors

2025: 3rd Place in Global Challenge for Safe and Secure LLMs (Track 2: Defence)
2024: 4th Place in Global Challenge for Safe and Secure LLMs (Track 1: Attack)
2018: 3rd Place in Stanford MURA Bone X-Ray Deep Learning Competition

Projects

2023 - 2026: Project manager & Tech leader of WP3: Development of Stable Robust and Secure Intelligent Systems for Autonomous Vehicles (Stage 1), AISG Robust AI Grand Challenge
2022 - 2024: Core member: MARIO: Multimodal AI-Driven Decision Making for Ophthalmology, RIE AME Programmatic Fund
2022 - 2024: Tech leader: Artificial Intelligence for Patient Self-Monitoring of Atopic Dermatitis, SingHealth Duke-NUS Paediatrics Academic Clinical Programme

Professional Services

2024: The algorithms I developed and the resulting products were selected for showcase at Singapore SWITCH 2024 .
2024: Invited to present research outcomes at the Healthcare AI Symposium 2024.
2025: Invited to present research outcomes at the Healthcare AI Symposium 2025.
ADimaster: Featured in IHPC Tech Hub , highlighting multiple research outcomes I contributed to.
Reviewer: IEEE TNNLS, IEEE TCDS, IEEE JBHI, Medical Image Analysis (MIA), Knowledge-Based Systems (KBS), and others.