2025 International Conference on Frontiers Technology in Circuits and Systems
(FTCS 2025)
November 21-23, 2025 | Chongqing, China
2025 International Conference on Frontiers Technology in Circuits and Systems
(FTCS 2025)
November 21-23, 2025 | Chongqing, China
Speaker 1 （Plenary Speech)
 | McGill University, Canada Speech title: Embracing Quantum: Graceful Disruption Entangled in Future Technology Bio: Zeljko Zilic received his Ph. D. and M. Sc. from the University of Toronto, and his B. Eng. from University of Zagreb, all in Electrical and Computer Engineering.Professor Zilic conducts research on various aspects of the design and test of Microsystems, including their applications for health and lifestyle improvements. He has published over 300 publications. He received five Best Paper Awards, including Best Paper Award from MobiHealth 2017, Wireless Mobile Communications and Healthcare 2014, Asian Symposium on Quality Electronic Design, Design and Verification Conference (DVCon) 2005 and Myril B. Reed Best Paper award from Midwest Symposium on Circuits and Systems. He has also received several Honorary Mention Awards, such as from IEEE Microelectronics Systems Education Conference, ETAN and CMC Symposia. Prof Zilic has led or participated in program committees for the High-level Design Validation and Test, International Symposium on Field Programmable Gate Arrays, International Test Conference, Silicon Debug and Diagnosis, Midwest Symposium on Circuit and Systems, NEWCAS and AQTR conferences, Electronic Circuits and Systems Conference, and Workshop on Open Source Test Technology. |
Speaker 2
 | IEEE Macau IES Chapter University of Macau, China Speech title: High-Efficiency Wireless Integrated On-Board Charger System for EVs Using Partial Power Conversion Speech abstract: With the continuous development of intelligent EVs, modern EVs are equipped with a wide range of electronic devices, including audio systems, smart chips, on-board navigation equipment, optical monitoring systems, and more. The increasing level of intelligence has led to higher power loss. Conventional fuel vehicles’ small batteries can no longer meet these requirements, necessitating larger-capacity auxiliary battery power supplies for EVs. In conventional conductive wired charging structures, the auxiliary battery is powered by an isolated low-voltage DC/DC converter connected to the power battery. During charging mode, the power battery is directly supplied by the grid, while the auxiliary battery receives power from the grid via the vehicle charger and subsequently through the low-voltage DC/DC converter, which serves as an isolation circuit. As EVs continue to develop, new demands have emerged regarding the size and efficiency of on-board chargers. Research has been conducted on integrating the design of the EV charger and the low-voltage DC/DC converter. Compared with the conventional conductive wired charger, wireless power transfer (WPT) technology enables non-contact power transmission through high-frequency alternating magnetic or electric fields, thereby eliminating the need for physical connections via metal conductors. Furthermore, for mobile electric devices such as EVs, wireless charging offers greater power supply flexibility, allowing immediate charging when parked and even dynamic charging during operation. This technology streamlines the power delivery process, enhances automation, and supports intelligent operation. Bio: Chi-Seng Lam received the Ph.D. degree in electrical and electronics engineering from the University of Macau (UM), Macau, China, in 2012. He completed the Clare Hall Study Programme at the University of Cambridge, Cambridge, U.K., in 2019. In 2013, he was a Postdoctoral Fellow with The Hong Kong Polytechnic University, Hong Kong, China. He is currently a Full Professor with the State Key Laboratory of Analog and Mixed-Signal VLSI and the Institute of Microelectronics, UM, and also with the Department of Electrical and Computer Engineering, Faculty of Science and Technology, UM. He has coauthored or co-edited five books and more than 220 technical journals and conference papers. He holds six U.S. and nine Chinese patents. His research interests include power electronic converters, power management integrated circuits, wireless power transfer, power quality compensation devices, and photovoltaic energy generation system. Prof. Lam is currently the Founding Chair of the IEEE Macau IES Chapter, Founding Chair of the IEEE TEC Macau Chapter, and the Vice-Chair of the IEEE IES Technical Committee on Power Electronics. He currently serves as an Associate Editor for the IEEE Transactions on Power Electronics, the IEEE Transactions on Industrial Electronics, the IEEE Journal of Emerging and Selected Topics in Power Electronics, and the IEEE Open Journal of the Industrial Electronics Society. He was awarded the 2024 IEEE Transactions on Industrial Electronics Outstanding Associate Editor, the 2022 and 2024 IEEE Transactions on Industrial Electronics Distinguished Reviewer, the 2024 IEEE Transactions on Power Electronics Outstanding Reviewer, and the 2024 Outstanding Reviewer by the IEEE Solid State Circuits Society. Prof. Lam is a Fellow of The Institution of Engineering and Technology (IET). |
Speaker 3
 | University of Macau, China Speech title: Design of Energy- and Area-Efficient Digital Neural Network Accelerators Speech abstract: A deep neural network is the mainstream approach in artificial intelligence. Convolutional neural networks (CNNs) and transformers are the two most widely adopted structures for various applications. However, an energy- and area-efficient accelerator is crucial for evaluating computing- and memory-intensive models. This talk explores key design strategies for designing energy- and area-efficient digital accelerators tailored to CNNs and transformers. It also presents practical insights through several FPGA-based and ASIC implementation case studies. Bio: Ka Fai Un's primary research focuses on radio frequency (RF), analog and mixed-signal CMOS integrated circuits, and artificial intelligence analog computing. |
Speaker 4
 | University of Macau, China Speech title: Area and Energy Efficient In-Memory and Near-Memory Computing Circuit-Algorithm Co-Design for AI at the Edge Speech abstract: Edge AI is rapidly evolving, and the need for energy- and area-efficient computing and memory solutions is more pressing than ever. This talk focuses on innovative circuit-algorithm co-design with in-memory computing, which is a promising circuit architecture to achieve low-cost and battery-efficient edge AI systems. Algorithms co-design enables innovative circuit techniques for significant out-of-the-box energy reduction for edge AI inferencing. We applied these techniques to applications like Keyword Spotting (KWS), speaker verification, and machine health monitoring, achieving state-of-the-art performance improvements. Circuit techniques like low-leakage 5T-SRAM, wirelessly distributed AI, TD-CNN, and AI-defined circuit systems are explored to tackle key challenges for future Edge AI. Bio: Wei-Han Yu received the Ph.D. degree from the University of Macau (UM) in 2018. From 2019 to 2021, he was a Visiting Scholar at the Murmann Mixed-Signal Group, Stanford University, USA. He has been an Assistant Professor with the State Key Laboratory of Analog and Mixed-Signal VLSI (AMSV), UM, since 2021. His research interests include edge AI, in-memory computing, switched capacitor circuits, energy-harvested RF transceivers, and neural interfaces. Dr. Yu received the IEEE SSCS Predoctoral Achievement Award in 2018. He has published over 50 top-tier microelectronic papers, including 13 papers in the IEEE JSSC and 7 papers at the IEEE ISSCC. |
