KEYNOTE Speakers

Prof. Xudong Jiang (IEEE Fellow)
Nanyang Technological University, Singapore

Biography: Xudong Jiang received the B.Eng. and M.Eng. from the University of Electronic Science and Technology of China (UESTC), and the Ph.D. degree from Helmut Schmidt University, Hamburg, Germany. From 1986 to 1993, he was a Lecturer with UESTC, where he received two Science and Technology Awards from the Ministry for Electronic Industry of China. From 1998 to 2004, he was with the Institute for Infocomm Research, A-Star, Singapore, as a Lead Scientist and the Head of the Biometrics Laboratory, where he developed a system that achieved the most efficiency and the second most accuracy at the International Fingerprint Verification Competition in 2000. He joined Nanyang Technological University (NTU), Singapore, as a Faculty Member, in 2004, and served as the Director of the Centre for Information Security from 2005 to 2011. Currently, he is a professor in NTU. Dr Jiang holds 7 patents and has authored over 200 papers with 2 papers in Nature Communications, 20 papers in Pattern Recognition and over 40+ papers in the IEEE journals, including 6 papers in IEEE Transactions on Pattern Analysis and Machine Intelligence and 14 papers in IEEE Transactions on Image Processing. Four of his papers have been listed as the top 1% highly cited papers in the academic field of Engineering by Essential Science Indicators. He served as IFS TC Member of the IEEE Signal Processing Society from 2015 to 2017, Associate Editor for IEEE Signal Processing Letter from 2014 to 2018, Associate Editor for IEEE Transactions on Image Processing from 2016 to 2020 and the founding editorial board member for IET Biometrics form 2012 to 2019. Dr Jiang is currently an IEEE Fellow and serves as Senior Area Editor for IEEE Transactions on Image Processing and Editor-in-Chief for IET Biometrics. His current research interests include image processing, pattern recognition, computer vision, machine learning, and biometrics.

Prof. Leida Li (National Young Talent)
Xidian University, China

Biography: Leida Li is a Full Professor at Xidian University, recognized as a National Young Talent. His research interests include computer vision, visual quality assessment, and computational aesthetics. He has published over 100 papers in top-tier journals and conferences like IEEE TPAMI, IEEE TIP, CVPR, ICCV, and AAAI, with about 10,000 citations. He has led five projects supported by the National Natural Science Foundation of China and has actively engaged in industry-academia collaborations with top companies such as Huawei, OPPO, and Tencent. He was awarded the "Outstanding Industry-Academia Collaboration Partner" by OPPO, and his research outcomes have been applied in smart phone and live-streaming cameras. He is an Associate Editor of IEEE Transactions on Image Processing (TIP) and Journal of Visual Communication and Image Representation(Best Associate Editor Award 2021/2023), and serves as Area Chair/Senior Program Committee member for top international conferences such as AAAI, IJCAI, and ACM MM. He is a Senior Member of IEEE/CCF/CSIG.

Prof. Jiantao Zhou
University of Macau, China

Speech Title: Towards Robust Learning-Based Multimedia Forensics

Abstract: In recent years, the proliferation of sophisticated multimedia generation and manipulation technologies, such as deepfakes and advanced image/video editing tools, has significantly blurred the line between authentic and fabricated content. As multimedia plays an increasingly crucial role in information dissemination, legal evidence, and social interactions, ensuring its integrity has become a pressing concern. How can we effectively distinguish genuine media from skilfully crafted forgeries, especially when traditional forensic techniques struggle to keep pace with rapidly evolving tampering methods? Moreover, the challenges are compounded by the degradation of forensic features during media transmission and the vulnerability of detection models to adversarial attacks. In the realm of multimedia forensics, learning-based approaches offer a promising avenue for tackling these complex issues. However, there is a pressing need to enhance their robustness against various distortions, obfuscation strategies, and dynamic threats. This talk explores the latest advancements in robust learning-based multimedia forensics, delving into novel methodologies designed to fortify detection capabilities. From developing innovative feature extraction techniques that can withstand transmission-induced degradation to creating resilient models that can counter adversarial manipulations, the presentation aims to outline a comprehensive research direction for achieving reliable and trustworthy multimedia forensics in an increasingly digital and deceptive world.

Biography: Dr. Jiantao Zhou is a Full Professor at the Department of Computer and Information Science, and the State Key Laboratory of Internet of Things for Smart City, University of Macau, where he also serves as the Director for Research Services and Knowledge Transfer Office. He graduated from the Hong Kong University of Science and Technology in 2009 with a PhD in Electrical and Computer Engineering. He was a Fulbright Junior Scholar at the University of Illinois at Urbana-Champaign (UIUC). Professor Zhou’s research focuses on AI security, multimedia information privacy protection and forensics, and intelligent multimedia information processing. He has published more than 200 papers in top journals such as IEEE T-PAMI, IEEE T-IP, IEEE T-SP, IEEE T-IFS, IEEE T-AC and other top conferences such as CVPR, ICCV, ICML, and AAAI. He currently serves as the Associate Editor for IEEE Trans. Multimedia and IEEE Trans. Dependable and Secure Computing, the top journals in the field of multimedia information processing and security and was the Editor-in-Chief of APSIPA Newsletters. He is the Chair for the Multimedia Systems and Applications Technical Committee in IEEE Circuits and Systems Society and was the TPC Co-Chair of ICME 2023 and the General-Chair of APSIPA ASC 2024. He received the 2022 Macau Science and Technology Award (Third Prize, Natural Science Award) and the 2023 Alibaba Outstanding Academic Cooperation Project Award.