Research

Overview

Continuously driven by emerging internet-of-things (IoT) applications, such as wireless sensor networks, wearable electronics, robotics, and human-machine interfaces, the next-generation IoT devices need to further enhance their capabilities by improving: 1) energy efficiency to achieve an optimum energy-performance tradeoff under resource-constrained conditions; 2) edge intelligence for evolving from passive components to smart systems with inference and interaction capabilities; 3) autonomy and miniaturization for ubiquitous deployment and operation without any human intervention.

Inspired by this vision, my current research areas include analog/digital/mixed-signal integrated circuits, energy harvesting and power management units, in-memory computing for edge AI, and systems-on-chip for ultra-low power IoT systems. My research mission is to make the next-generation IoT devices more energy-efficient, intelligent, and miniaturized to enable ubiquitous and autonomous deployment by leveraging advanced integrated circuit techniques with system optimizations from both power delivery and edge computing perspectives.

Efficient Energy Harvesting and Power Delivery for Self-Powered IoT SoCs

Highly Efficient Energy Harvesting and Power Management Systems

Sub-nW Power Management Solution for ULP IoT Systems

In-Memory Computing Accelerators for Edge AI

Characterizing the Bank-Level Accuracy vs. Energy Trade-off for SRAM-Based IMCs

Reconfigurable Neuromorphic IMC Architecture for Hybrid Neural Networks

Energy-Efficient SoC and Its Application for IoT Edge

Energy-Efficient IoT SoC using System-Level Power Management Techniques

Power Reduction of Miscellaneous Electric Loads using an Energy-Efficient SoC