Keynote 1: Noncontact Physiological Monitoring: Measurement Technologies, Signal Processing, and Clinical Applications
Assoc. Prof. Guanghao Sun
The University of Electro-Communications, Japan
Abstract:
Noncontact biomedical sensing is emerging as an important technology for unobtrusive and continuous monitoring of physiological information in healthcare and daily-life environments. This invited talk will present our recent research on noncontact and minimally intrusive measurement of vital signs using multimodal sensing technologies, including microwave radar, infrared thermography, RGB cameras, photoplethysmography (PPG), piezoelectric ballistocardiography (BCG) sensors, electrocardiography (ECG), and time-of-flight (ToF) sensors. Particular emphasis will be placed on signal and image processing techniques for extracting heart rate, respiration, body temperature, blood pressure, and other physiological indices from weak and noise-contaminated measurements. For example, microwave radar enables detection of minute body-surface movements associated with respiration and cardiac activity, while infrared thermography provides contact-free assessment of skin temperature. The talk will also introduce applications of these technologies to home healthcare, elderly monitoring, sleep monitoring, autonomic nervous system assessment based on heart-rate variability, infection-control and public-safety systems, and animal health monitoring.
Biography:
Dr. Guanghao Sun received the B.S. degree in medical engineering from Chiba University, Chiba, Japan, in 2011. He completed the Frontier Science Course supported by the Ministry of Education, Culture, Sports, Science & Technology (MEXT) in Japan, in 2011. His M.S. and Ph.D. degrees in system design engineering were received from Tokyo Metropolitan University, Tokyo, Japan, in 2013 and 2015, respectively. From April 2013 to September 2015, he was a Research Fellow with the Japan Society for the Promotion of Science. In 2015, he was with The University of Electro-Communications, Tokyo, Japan, as an Assistant Professor, where he became an Associate Professor in 2020. His research interests include non-contact bio-measurement, bio-signal processing, and design medical instrumentation. He is a Senior Member of IEEE Engineering in Medicine & Biology Society (IEEE-EMBS) and Japanese Society for Medical and Biological Engineering (JSMBE). He was the recipient of 2013 BES-SEC Design Silver Award for designing a multiple vital-signs based infection screening system and 2014 Chinese Government Award for Outstanding Self-financed Student Abroad.
Keynote 2: CMOS RF and Millimeter-Wave Sensing: Circuits, Antennas, and System Integration
Ass. Prof. Nguyen Ngoc Mai Khanh
The University of Nevada, Las Vegas, USA
Abstract:
Compact RF and millimeter-wave sensing systems require careful coordination of circuit design, antenna integration, and receiver sensitivity. This talk presents an overview of our research on CMOS sensing technologies, emphasizing three complementary directions: pulse transceivers with on-chip antennas, transmitter leakage cancellation, and on-glass antenna integration. The first part discusses CMOS pulse transceiver architectures and on-chip antennas for compact sensing, highlighting selected experimental results and the trade-offs among signal generation, radiation, and reception. The second part examines transmitter leakage as a limitation in detecting weak received signals and presents cancellation techniques developed to address this challenge. The third part explores on-glass antenna integration, discussing its opportunities and practical considerations for connecting antenna structures with CMOS circuits. Building on these contributions, the talk introduces recent simulation studies of a wide-tuning voltage-controlled oscillator with a frequency doubler for millimeter-wave sensing and a broadband low-noise amplifier for near-field magnetic probes. These studies illustrate ongoing efforts to balance bandwidth, noise, and power consumption. The talk concludes with lessons from prior implementations and future research directions toward compact, sensitive, and energy-efficient sensing platforms.
Biography:
Mai-Khanh Nguyen (Mike Nguyen) is an Assistant Professor in the Department of Electrical and Computer Engineering at the University of Nevada, Las Vegas, where he leads the Circuits, Packaging, and Intelligent Microsystems (CPIM) Lab. He received his Ph.D. from The University of Tokyo in 2011. Before joining UNLV, he held academic positions at The University of Tokyo and San José State University and worked at Marvell Technology. His research interests include analog and mixed-signal integrated circuits, RF and millimeter-wave transceivers, on-chip and on-glass antennas, and integrated sensing systems. He is an IEEE Senior Member.
Keynote 3: Designing for Power, Not Just Space and Performance
Dr. Le Quang Dam
General Director of Marvell Technology Vietnam
Abstract:
AI is scaling in compute – but the data center is scaling in bits. As AI systems grow larger, an enormous amount of data must move between processors, memory, and networks. The challenge is no longer simply how fast we can compute. It is how efficiently we can move all that data.
In this talk, I will explore how Marvell is addressing this challenge across the AI connectivity stack – from advanced SerDes and 1.6T optical DSPs such as Ara®, to Alaska® A active electrical cable retimers and Teralynx® Ethernet switch silicon. But connectivity is not one-size-fits-all. Different AI architectures and customer requirements demand different solutions, and Marvell combines its platform technologies with custom silicon and tailored solutions to optimize performance, bandwidth, latency, and power for specific applications.
We will look at the engineering trade-offs behind higher bandwidth and lower energy per bit – and how decisions made at the chip level can influence the efficiency of an entire AI data center. Then we will look ahead to the next generation of connectivity, including 1.6T and beyond, 2nm and below technologies, silicon photonics, and new optical architectures that bring compute, memory, and connectivity closer together.
The question is simple: How do we move more data, faster, without consuming more power? And how can we design connectivity around the needs of each AI system to build infrastructure that is not only more powerful, but also more efficient?
Biography:
Quang-Dam Le (nicknamed QD) joined Marvell in 2011, and held different positions such as Technical Director, Senior Director, Associate Vice President, and presently, he is the General Director of Marvell Technology Vietnam. He was graduated with a Bachelor of Science (B.Sc.) degree from Ho Chi Minh City University of Science (HCMUS) in 1988, a Master (MSc.) degree in Physics in Canada in 1993 , and a Doctorate (Ph.D.) degree in Signal Processing (Artificial Intelligence) in Canada in 1996, before starting his career in the semiconductor industry.
QD began his career as an algorithm designer for all Digital Signal Processing (DSP) IPs for Miranda Technologies, thereafter Gennum Corporation as Senior Video System Architect, and went on to join ATI Technologies Inc (acquired later by Advanced Micro Devices – AMD) as Senior Manager to manage the DSP teams, responsible for Markham (Canada), Bangalore (India), Shanghai (China) and Munich (Germany). Just prior to Marvell, he was a Senior Principal Scientist with Broadcom. He has strong interest in System Architecture, Signal Processing and Artificial Intelligence.