Dr. Haodong Li received the B.E. and Ph.D. degrees from Sun Yat-sen University, Guangzhou, China, in 2012 and 2017, respectively. He is currently an Assistant Professor with the College of Electronics and Information Engineering, Shenzhen University, Shenzhen, China. His research interests include multimedia forensics, intelligent information processing, and machine learning. He is a member of Technical Committee on Digital Media Forensics and Security of CSIG.

[1]2012-2017, Ph.D., Sun Yat-sen University

[2]2008-2012, B.E. Sun Yat-sen University

[1]2020-Present, Assistant Professor, Shenzhen University

[2]2017-2020, Postdoctoral Fellow, Shenzhen University

[1]EURASIP Best Paper Award, 2024.

[2]First Prize of Outstanding Paper Award, Computer Academy of Guangdong, 2023.

[1]Multimedia Forensics and Security

[2]Multimedia Signal Processing

[1]Peiyu Zhuang, Haodong Li*, Rui Yang, Jiwu Huang. ReLoc: A restoration-assisted framework for robust image tampering localization. IEEE Transactions on Information Forensics and Security, 18: 5243–5257, 2023. (CCF-A)

[2]Peiyu Zhuang, Haodong Li*, Shunquan Tan, Bin Li, and Jiwu Huang. Image tampering localization using a dense fully convolutional network. IEEE Transactions on Information Forensics and Security, 16: 2986–2999, 2021. (CCF-A)

[3]Haodong Li, Bin Li, Shunquan Tan, and Jiwu Huang, Identification of deep network generated images using disparities in color components, Signal Processing, 174:107616, 2020. (2024 EURASIP Best Paper)

[4]Haodong Li and Jiwu Huang. Localization of deep inpainting using high-pass fully convolutional network. In IEEE International Conference on Computer Vision (ICCV), pp. 8300–8309, 2019. (CCF-A)

[5]Haodong Li, Weiqi Luo, Xiaoqing Qiu, and Jiwu Huang. Identification of various image operations using residual-based features. IEEE Transactions on Circuits and Systems for Video Technology, 28(1):31–45, 2018. (CCF-B)

[6]Haodong Li, Weiqi Luo, Xiaoqing Qiu, and Jiwu Huang. Image forgery localization via integrating tampering possibility maps. IEEE Transactions on Information Forensics and Security, 12(5):1240–1252, 2017. (CCF-A)

[7]Haodong Li, Weiqi Luo, and Jiwu Huang. Localization of diffusion-based inpainting in digital images. IEEE Transactions on Information Forensics and Security, 12(12):3050–3064, 2017. (CCF-A)

[8]Changsheng Chen, Xijin Li, Baoying Chen, Haodong Li*. A distortion model guided adversarial surrogate for recaptured document detection. Pattern Recognition. 151:110433, 2024. (CCF-B)

[9]Bin Li, Bowei Zheng, Haodong Li*, and Yanran Li. Detail-enhanced image inpainting based on discrete wavelet transforms. Signal Processing. 189: 108278, 2021.

[10]Shujin Wei, Haodong Li*, and Jiwu Huang. Deep video inpainting localization using spatial and temporal traces. IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). pp. 8957-8961, 2022. (CCF-B)

[1]Research on Digital Image Forgery Localization in Complex Situations. NSFC.

[2]Robust Image Tampering Forensics Technology against Lossy Post-Processing. Guangdong Basic and Applied Basic Research Foundation.

[3]Research on Robust Image Tampering Forensics Technology for Real Scenes. Shenzhen Scientific Research Foundation for Newly Introduced Advanced Talents.