Research
Applications
Intelligent Multiphysics Sensing and Imaging Systems
Emerging applications in healthcare, autonomy, and environmental intelligence demand a step-function leap in sensing performance. These systems must perceive, interpret, and act far beyond today’s limits imposed by the physics of single-modality technologies. Conventional architectures remain fundamentally constrained—limited in resolution, dynamic range, robustness, and their ability to penetrate or reconstruct complex media such as biological tissue, air–water boundaries, or subsurface structures. Addressing this next frontier requires new hybrid, intelligent sensing systems that transcend existing physical and algorithmic boundaries.
To overcome these barriers, our group develops multi-physics, multi-modal end-to-end sensing systems that integrate the complementary strengths of electromagnetic (EM/RF), ultrasonic (US), and optical modalities. Our approach spans the entire sensing hardware-algorithms/software stack—from manipulating waves at the physical layer and designing custom ICs for detection at the noise floor and scalable array architectures, to advancing signal processing and machine learning for adaptive, cross-modal fusion. By uniting diverse physical principles, we have demonstrated new capabilities in 3D imaging, kinematics-based world understanding, cross-boundary imaging, and non-contact subsurface sensing.
Projects
Adaptive and Closed-Loop Intelligent Sensing and Inference Systems
Recent advances in large-scale transformer models and high-resolution sensors (cameras, lidars, radars) have enabled AI systems that autonomously collect, interpret, and act on data—powering technologies from smartphones and wearables to autonomous vehicles, robotics, and AR/VR.
However, these capabilities come at steep and increasingly unsustainable costs. Training and inference of large models require enormous computational and energy resources, while the explosion of sensory data and the associated compute far exceeds the capacity of conventional edge devices. Shifting this burden to the cloud is not a long-term solution either: even if latency, bandwidth, and privacy constraints could be ignored, the aggregate energy footprint of hyperscale cloud computing is growing along an unsustainable trajectory. Thus, we face two fundamental bottlenecks—we cannot feasibly bring these massive models to the edge, and we cannot indefinitely absorb their demands in the cloud.
Inspired by the human brain—a predictive, feedback-driven system that processes vast sensory inputs and adaptively integrates multimodal information—we propose closed-loop adaptive perception systems. By dynamically coordinating sensing and inference through real-time feedback, these systems aim to achieve brain-like efficiency: delivering intelligence at the physical edge while dramatically improving the performance–power trade-off across the entire compute hierarchy.
Projects
Device and Circuit Innovations
Rapid advancements of silicon technology in the past decade have enabled significant circuit- and device-level innovation in virtually every modern scientific domain, spanning medical devices, environmental monitoring, IoT networks, and high frequency sensing and communication systems. As society increasingly relies on interconnected devices and real-time data transmission, the demand for power-efficient, reliable, and sustainable electronic systems has reached an apex. Our lab seeks to develop pioneering integrated solutions for such diverse fields, with projects including ultra-low-power device design, high-frequency (e.g., mmWave) circuits for high-resolution sensing and communication applications, and implantable/ingestible electronics for real-time, point-of-care biomedical monitoring.
- Ultra-Low Power Circuits & Systems for IoT Networks: Our lab develops innovative approaches in wirelessly powered sensor nodes, combining RF and acoustics with low-power circuit techniques to enable power-efficient, user-friendly systems across multiple domains.
- High-Frequency & mmWave Sensing and Communications: This thrust focuses on the development of advanced integrated circuit architectures and high-frequency links, including MIMO arrays and multi-sensor solutions, to enhance the efficiency of both wireless and wireline systems in diverse applications, ranging from autonomous vehicles to edge-based wearables.
- Biomedical Devices and Implant Systems: Our work in wireless implantable/ingestible devices and systems investigates various modalities for wireless power delivery, including both RF and ultrasound, leveraging novel circuit techniques to design devices for applications ranging from analyte sensing and drug delivery to neural/retinal interfaces.
Projects
Biomedical Circuits and Systems
Nyquist-Rate Healthcare: Closing the Sub-Sampling Gap in Monitoring and Closed-Loop Therapy with IoT Devices and Processing at the Edge
Recent advances in healthcare technology have primarily focused on therapeutics, interventional procedures, and late-stage or “post-symptom” diagnostics. These developments have significantly improved survival rates and quality of life. However, this progress remains unsustainable, as national healthcare costs continue to escalate and outcomes for several critical diseases remain inadequate. Cancer serves as a prominent example—despite decades of technological innovation in diagnostic imaging, mortality rates have seen limited improvement.
This research seeks to bridge the gap between technology and the human body through new systems that (1) enable continuous, “Nyquist-rate” imaging and screening for predictive and preventive care, and (2) develop smart implants for precision monitoring and closed-loop therapeutic intervention. Drawing inspiration from the Internet of Things (IoT), the work integrates advanced sensing and edge processing technologies to improve health outcomes through real-time, context-aware data.Continuous, preventive monitoring has the potential to redefine how disease is detected, understood, and treated. Unlike current health assessments—which are infrequent and low in temporal “resolution”—the envisioned systems operate more like advanced electronic infrastructures that are constantly calibrated and optimized. Several example projects exemplify this vision, including new sensing and stimulation platforms that function as implants, ingestibles, or wearables designed for seamless and intelligent interaction with the human body.