Keynote Speakers
Prof. Qun Jin,
Waseda University, Japan
Prof. Qun Jin is a professor in the Department of Human Informatics and Cognitive Sciences, Faculty of Human Sciences, Waseda University, Japan. He has been extensively engaged in research works in the fields of computer science, information systems, and human informatics, with a focus on understanding and supporting humans through convergent research. His recent research interests cover behavior and cognitive informatics, big data, artificial intelligence and machine learning, LLM and generative AI, AI agents, blockchain, metaverse, cyber-physical-social systems, and applications in healthcare and learning support. He is a foreign fellow of the Engineering Academy of Japan (EAJ) and a fellow of the Asia-Pacific Artificial Intelligence Association (AAIA).
Prof. Jianhua Ma,
Hosei University, Japan
Jianhua Ma is a professor in the Faculty of Computer and Information Sciences, and was a director in the Institute of Integrated Science and Technology (IIST), Hosei University, Japan. He is one of pioneers in research on Hyper World and Cyber World (CW) since 1996. He first proposed Ubiquitous Intelligence (UI) towards Smart World (SW), which he envisioned in 2004, and was featured in the European ID People Magazine in 2005. He has conducted several unique CW-related projects including the Cyber Individual (Cyber-I), which was highlighted on the IEEE Computing Now in 2011. He has founded IEEE Conferences on Ubiquitous Intelligence and Computing (UIC), Pervasive Intelligence and Computing (PICom), Cyber Physical and Social Computing (CPSCom), Internet of Things (iThings), and Internet of People (IoP). He is a chair of IEEE SC Technical Committee on Hyper-Intelligence, a co-chair of IEEE SMC Technical Committee on Cybermatics, and a founder of IEEE CIS Technical Committee on Smart World.
Invited Speakers
Prof. Hongping Gan, Northwestern Polytechnical University, China
Hongping Gan is an Associate Professor and Ph.D. Supervisor at the School of Software, Northwestern Polytechnical University, and a member of the Professional Committee on Data Security Industry of China. In the past three years, he has published more than 30 high-quality papers as the first or corresponding author in leading international journals and top conferences including IEEE TIP, TGRS, TCI, TCYB, TCSVT, TCE, TNSM, CVPR and AAAI. He has been the principal investigator of several research projects, including the General Program and Youth Program of the National Natural Science Foundation of China, the Natural Science Foundation of Shaanxi Province, and the Technological Frontier Special Project. He was invited to attend the 2021 China Airshow in Zhuhai, the 2023 World UAV Congress and the 2024 China Defense Electronics Exhibition, where he delivered invited presentations.
Speech title: Interpretable Deep Unfolding Networks for Compressive Sensing
Abstract: In the era of big data, compressive sensing (CS) has provided a revolutionary solution for efficient signal acquisition and reconstruction. However, traditional algorithms have long been constrained by bottlenecks such as complex manual parameter tuning, low computational efficiency, and insufficient real-time performance. In recent years, deep unfolding networks (DUN), by integrating the dual advantages of model-driven optimization and data-driven learning, have significantly improved reconstruction speed and accuracy, emerging as a cutting-edge breakthrough in the field of CS. Therefore, this report will analyze state-of-the-art DUN method for CS, explain several classic network architectures, and explore future development trends of this technology.
