Hello! I am Dongliang Zhu (朱栋梁) — thank you for visiting my homepage. I am currently a Research Scientist at the School of Computing and Information Systems, Singapore Management University (SMU), working with Prof. Shengfeng He. I received my Ph.D. degree in Computer Science from Wuhan University (WHU) in June 2026, under the supervision of Prof. Ruimin Hu. From August 2025 to June 2026, I was also a visiting research intern at Great Bay University (GBU), advised by Prof. Zitong Yu. In addition, I was also fortunate to receive help from Prof. Mang Ye, Prof. Zheng Wang, and Prof. Liang Liao.

My research interests include AI-generated content (AIGC) detection, multimodal deception detection, and video anomaly detection. My long-term goal is to build trustworthy and secure AI perception systems that can defend against deepfakes, deceptive behaviors, and anomalous threats in real-world environments. I am always open to research discussions and potential collaborations. If you are interested in my research topics or just want to have a chat, please feel free to contact me via Email.

Prior to my doctoral studies, I received my M.S. degree from Hubei University of Technology in September 2021, where I was co-advised by Prof. Chunyan Zeng and Prof. Zhifeng Wang. My master's research focused on deep learning for speech recognition.

🤗 News

2026.06: 🎓 I successfully received my Ph.D. degree in Computer Science from Wuhan University!
2026.06: 🎉🎉🎉 Two papers, MoMCE: Mixture of Modality and Cue Experts for Multimodal Deception Detection and DecepGPT: Schema-Driven Deception Detection with Multicultural Datasets and Robust Multimodal Learning, were accepted to ECCV 2026!
2026.06: 🎉🎉🎉 Our paper Deception Detection Meets Vision-Language Models was accepted by the International Journal of Computer Vision (IJCV)!
2025.05: 🎉🎉🎉 Our paper Detecting Deceptive Behavior via Learning Relation-Aware Visual Representations was accepted by IEEE Transactions on Information Forensics and Security (TIFS)!
2023.09: 🎉🎉🎉 Our paper Cross-Illumination Video Anomaly Detection Benchmark was accepted to ACM Multimedia 2023!

📖 Selected Publications

* indicates equal contribution

MoMCE: Mixture of Modality and Cue Experts for Multimodal Deception Detection. ECCV 2026.

Dongliang Zhu, Ruimin Hu, Zitong Yu, Xiaobao Guo, and others.

[Paper] [Code]

DecepGPT: schema-driven deception detection with multicultural datasets and robust multimodal learning. ECCV 2026.

Jiajian Huang*, Dongliang Zhu*, Zitong Yu, Hui Ma, and others.

[Paper] [Code]

Deception Detection Meets Vision-Language Models. IJCV 2026.

Dongliang Zhu, Ruimin Hu, Mei Wang, and others.

[Paper] [Code]

Detecting Deceptive Behavior via Learning Relation-Aware Visual Representations. IEEE TIFS 2025.

Dongliang Zhu, Chi Zhang, Ruimin Hu, and others.

[Paper] [Code]

Cross-Illumination Video Anomaly Detection Benchmark. ACM MM 2023.

Dongliang Zhu, Ruimin Hu, Shengli Song, and others.

[Paper] [Code]

🏆 Honors and Awards

2025 Huawei Scholarship, Wuhan University.
2024 China Yangtze Power Scholarship, Wuhan University.
2021 Outstanding Graduate, Hubei University of Technology.
2020 First-Class Scholarship, Hubei University of Technology.

🏫 Educations

2021.06 – 2026.06, Wuhan University, Wuhan, China, Ph.D. in Computer Science, supervised by Prof. Ruimin Hu.
2025.08 – 2026.06, Great Bay University (visiting), advised by Prof. Zitong Yu.
2018.09 – 2021.09, Hubei University of Technology, Wuhan, China, M.S. in Computer Science, co-advised by Prof. Chunyan Zeng and Prof. Zhifeng Wang.

💬 Services

Program Committee Member: AAAI 2026, AAAI 2027, ACM Multimedia.
Reviewer: Expert Systems with Applications (ESWA), Pattern Recognition (PR), IEEE Transactions on Information Forensics and Security (TIFS), International Journal of Computer Vision (IJCV), Pacific Graphics 2026, Journal on Information Security.