The 6th Sun Yat-sen University and SSCS-Guangzhou Forum on Integrated Circuits Successfully Concludes
On November 22, 2025, the 6th Sun Yat-sen University and SSCS-Guangzhou Forum on Integrated Circuits was successfully held at Sun Yat-sen University's East Campus. The forum brought together numerous renowned experts, providing an excellent platform for exchange and collaboration across various integrated circuit research fields, while also summarizing the accomplishments of the SSCS-Guangzhou Section over the past year.
Fig 1. The Group Photo of the 6th Sun Yat-sen University and SSCS-Guangzhou Forum on Integrated Circuits.
On the morning of the event, ten outstanding students from the School of Electronics and Information Technology, the School of Integrated Circuits, and the School of Microelectronics Science and Technology at Sun Yat-sen University delivered excellent presentations. Their reports covered multiple research areas such as analog integrated circuits, photonic chips, and hardware accelerators, showcasing the latest research findings to the attending faculty and students.
In the afternoon, dozens of invited experts from academia and industry gathered at the forum venue. Professor Dihu Chen summarized the achievements of the IC Center and the SSCS-Guangzhou Section over the past year. Afterward, experts from academia and industry shared the latest research findings and challenges in big data computing, high-speed signals & RF, and power management ICs. Professor Zhongfeng Wang demonstrated how to design low-power DNN hardware. Professor Jiang Xu highlighted his team's research approach in high-speed, large-scale optical switching. Researcher Liyuan Liu presented his team's abundant achievements on AI vision ICs. Professor Xiuyin Zhang shared insights into his team's expertise in designing millimeter-wave front-end chips for 5G frequency bands. Dr. Sang Liu, leveraging the new 90-GHz oscilloscope as a starting point, shared his observations on the similarities and differences between industry and academia. Dr. Yuanfei Wang then presented his latest research findings on switched-capacitor DC-DC converters. Professor Qiujin Chen shared research methodologies and insights on radio-frequency energy harvesting.
Fig 2. The seven invited expert speakers shared the latest research findings and challenges across multiple fields.
During the tea break between presentations, we displayed over 30 student posters collected from three schools of Sun Yat-sen University. LongSight Technology Ltd. also showcased its new 90-GHz oscilloscope. At the conclusion of the event, Professor Zhihua Wang from Tsinghua University delivered an inspiring closing speech. He extended his congratulations on the successful organization of the forum and emphasized to the attending students the importance of participating in academic forums.
Date and Time
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- 132 Outer Ring East Road, University City, Panyu District
- Guangzhou, Guangdong
- China 510006
- Building: South lab Building of East campus, SYSU
- Room Number: E301
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- Co-sponsored by Jianping Guo
- Starts 11 November 2025 04:00 AM UTC
- Ends 22 November 2025 09:40 AM UTC
- No Admission Charge
Speakers
Prof. Chen of Sun Yat-sen University
A Summary of Achievements of the IC Center and the SSCS-Guangzhou Section
Over the past year, the SSCS-Guangzhou Section has expanded in both size and professionalism. In research, the section has made significant progress with publications in top-tier academic journals and conferences, including JSSC, ISSCC, and CICC.
Biography:
Professor and Doctoral Supervisor, a Sun Yat-sen University Distinguished Teacher and Outstanding Educator of Southern Guangdong Province, currently serves as Director of the Guangdong Provincial Engineering Technology Research Center for Integrated Circuits. He earned his Bachelor's and Master's degrees from Sichuan University, specializing in Semiconductor Physics and Semiconductor Physics & Devices respectively, and completed his Ph.D. in Electronic Engineering at The Chinese University of Hong Kong. His research encompasses integrated circuit design methodologies, SoC digital chip design, deep learning with hardware acceleration, functional nanomaterials, micro/nano-sensor devices, and biochips.
Prof. Wang of Sun Yat-sen University
Low-Power DNN Hardware Design and Optimization
Emerging large-scale AI models pose significant challenges to the memory, computational capacity, and energy consumption of AI hardware. Relying solely on Moore's Law-driven improvements in hardware performance is no longer sufficient to address these challenges. Therefore, it is necessary to leverage methods such as mixed-precision and quantization, neural architecture search (NAS), sparse acceleration techniques, and hardware-software co-design to enhance the capabilities of AI hardware and meet the demands of these advanced models.
Biography:
A National High-Level Talent and IEEE/AIAA Fellow, he earned his Bachelor's and Master's degrees from the Department of Automation at Tsinghua University. He received his Ph.D. in 2000 from the Department of Electrical and Computer Engineering at the University of Minnesota. His research primarily focuses on modern error-correcting code design and implementation, high-speed wired and wireless communication systems, co-optimization of artificial intelligence algorithms and hardware architectures, and post-quantum cryptography (PQC) and computer architecture security.
Prof. Xu of Hong Kong University of Science and Technology (Guangzhou)
Optoelectronic Chips and Systems
Artificial intelligence is spearheading a new industrial revolution in the information era, with its development and applications driving an exponential increase in computational demands. However, relying solely on the gradually slowing Moore's Law and advanced manufacturing processes can no longer meet the high-speed processing requirements of AI for massive data. Consequently, leading global chip companies are unanimously pursuing research and development in optoelectronic fusion chips and systems, which integrate photons and electrons. These systems are regarded as the next-generation AI computing technology beyond "Moore's Law," capable of significantly enhancing computational power and energy efficiency. Based on nearly two decades of exploration in optoelectronic fusion technology, this presentation will introduce some advancements in leveraging optoelectronic fusion to improve system performance. Optoelectronic fusion will not only revitalize computing systems in the post-Moore's Law era but also bring new opportunities for applications, architectures, designs, and design automation tools.
Biography:
Professor Jiang Xu is a tenured professor at the Hong Kong University of Science and Technology (Guangzhou), where he serves as the Founding Head of the Microelectronics Thrust and Director of both the Guangdong Provincial Industry-Education Integration Innovation Platform for Integrated Circuits and the Guangzhou Key Laboratory for EDA. He earned his Ph.D. from Princeton University in the United States and previously held positions at Bell Labs and the U.S. laboratory of NEC. Under his mentorship, his doctoral and postdoctoral graduates have gone on to become professors at universities in China, the United States, France, Canada, and Singapore, or hold key positions in the chip development teams of leading companies such as Huawei, Intel, Qualcomm, and Apple.
Prof. Liu of Chinese Academy of Sciences
Artificial Intelligence Vision Chips
The integration of visual sensing and processing can break away from the traditional separation of image sensors and image processors. Research on highly integrated, low-power, compact, and high-speed AI vision chips addresses the challenge of real-time image data processing. In 3D depth image sensors, the adoption of CMOS single-photon image sensors combined with pulsed vision processors enables high resolution, eliminates the need for multiplication operations, and offers advantages of small footprint and low power consumption, making them suitable for edge applications.
Biography:
Researcher at the Institute of Semiconductors, Chinese Academy of Sciences, and Professor at the University of Chinese Academy of Sciences. He obtained his Ph.D. in Engineering from Tsinghua University in 2010, conducted postdoctoral research at the Department of Electronic Engineering of Tsinghua University from 2010 to 2012, and joined the State Key Laboratory of Superlattices and Microstructures at the Institute of Semiconductors, Chinese Academy of Sciences as an Associate Researcher in July 2012. In January 2018, he was appointed as a Researcher at the State Key Laboratory of Superlattices and Microstructures. His research primarily focuses on artificial intelligence vision chips, leveraging the platform of the Institute of Semiconductors to investigate artificial visual perception devices and circuits, novel vision sensors, edge vision processors, and sensor/processor integration technologies.
Prof. Zhang of South China University of Technology
Broadband and Multi-Functional Microwave/Millimeter-Wave Chips
Microwave and millimeter-wave chips are critical components in wireless communication systems, with front-end chips significantly impacting system power efficiency, linearity, and noise performance. This presentation introduces some of our research group's work on broadband and multi-functional millimeter-wave CMOS front-end chips. Additionally, it covers our group's advancements in compound semiconductor-based broadband and multi-functional chips.
Biography:
Currently serving as the Executive Vice Dean of the School of Microelectronics at South China University of Technology, he is a recipient of the National Science Fund for Distinguished Young Scholars, a Cheung Kong Scholar, an IEEE Fellow, and a member of the Science and Technology Commission of the Ministry of Education. He also directs the Ministry of Education's Engineering Research Center for "Short-Range Wireless Communication and Networks." His primary research areas include RF chips, devices and front-end systems, antennas, intelligent wireless sensing and integrated sensing-communication, as well as the Internet of Things (IoT).
Prof. Liu of LongSight Technology Ltd.
Measurement and Contemplation on High-Frequency and High-Speed Signals
This report is grounded in the development patterns and current landscape of the electronic information instrumentation industry. Centered on the testing demands for high-speed and high-frequency signals, it systematically analyzes the relentless pursuit of the best performance in key indicators such as bandwidth, noise, and efficiency in high-end instruments. Furthermore, it offers in-depth reflections on the comprehensive challenges, innovation requirements, and countermeasures for extreme testing and characterization facing next-generation high-end instrumentation.
Biography:
He earned his Ph.D. in Engineering in 2000 and assumed the role of CEO at LongSight Technology Ltd. in 2023, taking full responsibility for the company's operations and management. Under his leadership, the team has achieved multiple technological breakthroughs and successful commercial applications in high-end instruments across cutting-edge fields such as time-domain, frequency-domain, and artificial intelligence computing networks.
Dr. Wang of University of Macau
Continuously Variable Ratio Switched-Capacitor Power Conversion Chip
This presentation introduces a reconfigurable continuously variable ratio switched-capacitor converter (RCSC) with adjustable flying capacitor voltage (VCF) step sizes. It begins by analyzing the operational mechanism of conventional continuously variable ratio switched-capacitor converters (CSC) and identifies the reasons for their efficiency degradation across a wide voltage conversion ratio (VCR) range. The proposed RCSC reconfigures and standardizes the step sizes of the flying capacitor voltage according to the VCR, thereby maximizing efficiency over a broader VCR range. A gate control signal generation scheme is introduced to significantly reduce the implementation cost of the reconfiguration function. The RCSC can operate in both step-up and step-down modes and is compatible with maximum power point tracking (MPPT) applications in energy harvesting systems. Test results based on a 65-nm CMOS process demonstrate that the RCSC with 34 VCF step sizes achieves a peak efficiency of 90% and maintains efficiency above 75% across the widest normalized VCR range.
Biography:
Dr. Wang earned his Ph.D. from the University of Electronic Science and Technology of China in 2020. He conducted postdoctoral research at the University of Science and Technology of China & Zhuhai UM Science and Technology Research Institute from 2021 to 2022. In 2022, he joined the University of Macau as a postdoctoral researcher and is scheduled to conduct an academic visit to the Hong Kong University of Science and Technology in 2025. His research primarily focuses on energy harvesting system design, continuously variable ratio switched-capacitor converters, and IVR power management IC design.
Prof. Chen of Xidian University
High-Performance RF Energy Harvesting Systems
The design of radio frequency (RF) energy harvesting systems faces numerous challenges, with different considerations for high-power and low-power scenarios. Moreover, due to their inherent nonlinear characteristics, traditional maximum power point tracking (MPPT) strategies cannot be directly applied to RF energy harvesting systems. This presentation will systematically introduce the application scenarios, fundamental theoretical principles, and cutting-edge integrated circuit design techniques for RF energy harvesting systems, covering key technologies such as high-efficiency energy conversion, RF rectifier design, and maximum power point tracking (MPPT).
Biography:
Prof. Chen is a professor at Xidian University, a recipient of the National Young Talent Program (Overseas), and a doctoral supervisor. He earned his Bachelor's degree in Microelectronics Science and Engineering from Southern University of Science and Technology in 2020 and received his Ph.D. in Electrical and Computer Engineering from the University of Macau in 2024. From 2024 to 2025, he worked as a postdoctoral researcher at the State Key Laboratory of Microelectronics at the University of Macau. His main research interests include power converter design, power management IC design, and wireless power transfer circuits and systems.
Prof. Wang of Tsinghua University
The Closing Speech of the 6th SSCS-Guangzhou Section IC Academic Forum
Prof. Wang extended his congratulations on the successful organization of the academic forum and emphasized to the attending students the importance of participating in academic conferences. Prof. Wang encouraged students aspiring to join the industry to actively present their work at such forums, noting that presenting here is an even more valuable opportunity than a company interview. For those pursuing a future in academia, he highlighted that delivering presentations is a crucial way to gain recognition within the academic community. Furthermore, Professor Wang urged all students to actively share their outstanding future research findings with the next generation of scholars.
Biography:
Prof. Wang graduated from the Department of Electronic Engineering at Tsinghua University, earning his Bachelor's degree in 1983, Master's in 1985, and Ph.D. in 1990. Between 1992 and 1994, he conducted research as a visiting scholar at Carnegie Mellon University in the United States and KU Leuven in Belgium. From 2014 to 2015, he served as a visiting professor at the Hong Kong University of Science and Technology. His research primarily focuses on CMOS RFIC and biomedical applications.
