7th International Conference on Signal Processing and Information Communications

Dr. Chua-Chin Wang received the Ph.D. degree in electrical engineering from SUNY (State University of New York) at Stony Brook, USA, in 1992. He then joined Department of Electrical Engineering, National Sun Yat-Sen University (NSYSU), Taiwan. He was Chairman of this department during 2009 - 2012. He was CEO of Operation Center of Industry-University Cooperation, NSYSU, in 2012-2014. He was appointed to be VP of Office of Industrial Collaboration and Continuing Education Affairs, from 2014 to 2015. He was elected as Dean of Engineering College during 2014-2017. He became as Director General of Underwater Vehicle R&D Center since 2018. He was Vice President, Office of Research and Development, NSYSU from 2021-2024. Dr. Wang’s research interests include memory and logic circuit design, communication circuit design, bio-medical circuits, and particularly interfacing I/O circuits. He also won Distinguished Electrical Engineering Professor Award of Chinese Institute of Electrical Engineers in 2007. In 2010, he was honored to be Distinguished Professor of National Sun Yat-Sen University. In 2012, he won “Distinguished Engineering Professor” Award of Chinese Institute of Engineers and Outstanding Research Award of NSYSU. He became IET Fellow in 2012. He was named as ASE Chair Professor in 2013 for the recognition of his achievement in the area of VLSI design and contribution to industry technology development. He won Outstanding Technical Achievement Award of IEEE Tainan Section in 2018. Prof. Wang has devoted himself for many IEEE services. He was Tainan Chapter Chair of IEEE Circuits and Systems Society (CASS) in 2007-2008. He was also the founding Tainan Chair of IEEE Solid-State Circuits Society (SSCS) for 2007-2008, and the founding Consultant of IEEE NSYSU Student Branch. He was elected to be Vice Chair of IEEE Tainan Section in 2012. He was elected to be Chair of IEEE CASS Nanoelectronics and Giga-scale Systems (NG) Technical Committee to serve during 2008-2009. He has been invited to be Associate Editors of IEEE Trans. on TCAS-I (2010-2013) and TCAS-II (2010-2011). He was General Chair of 2012 IEEE Asia Pacific Conference on Circuits and Systems (APCCAS), which is the flagship conference of IEEE CASS Region 10. Dr. Ralph Gerard B. Sangalang received his B.S. degree in Electronics and Communications Engineering and M.S. in Electronics Engineering at Batangas State University, Philippines. He obtained the Ph.D. in Electrical Engineering and Ph.D. in Electronics Engineering under the double degree program at National Sun Yat-Sen University, Taiwan and Batangas State University- The National Engineering University, Philippines in 2023 and 2024, respectively. He was awarded the Yeh Kung-Chie Memorial Scholarship Award at NSYSU in 2023. Currently, he is an Assistant Professor at Batangas State University-TNEU where he also the head of the Electronic Systems Research Center (ESRC). He is also the chairperson of the graduate programs in Electronics Engineering (ECE) at BatStateU-TNEU. He was the Program Chair of BS Electronics Engineering during 2017-2021 and Interim Program Chair of the BS Biomedical Engineering. He is a member of Batangas State University's CenTraL or the Center for Transformative Learning. He has served as reviewer in ISCAS, AICAS, ISIEA, ISBI, CSSP, JSPS, IJE, Kybernetika, and IJCDS. His research interests include memory design, AI circuits, digital systems, control systems, computational modelling, fractional circuits, and engineering education.

• Introduction.- Adaptive Filtering & Signal Processing, Ad-Hoc and Sensor Networks.- Analog and Mixed Signal Processing.- Array Signal Processing.- Audio and Electroacoustics.- Audio/Speech Processing and Coding.- Bioimaging and Signal Processing.- Biometrics & Authentification.- Biosignal Processing & Understanding.- Communication and Broadband Networks.- Computer Vision & Virtual Reality.- Cryptography and Network Security.- Design and Implementation of Signal Processing Systems.- Compressive sensing.- machine learning methods for communications and signal processing.- Conclusion.