Interdiscipline expertise
through knowledge and experience
Interdiscipline expertise
through knowledge and experience
Robotics and Smart Health
My research advances the convergence of robotics and healthcare through intelligent sensing systems that enhance human-robot interaction and medical diagnostics. I have developed multimodal sensory electronic skin that enables synchronized haptic interfaces for augmented human-robot interaction, while artificial compound eye technology provides robots with advanced spatiotemporal perception and cognition capabilities in three-dimensional space. In healthcare applications, I have created integrated biosensors with near-sensor AI algorithms for rapid virus detection and developed adaptive multimodal biomedical sensing systems for early recognition of neurodegenerative disorders, particularly Parkinson's disease. These innovations demonstrate how my robotics-inspired sensing approach can transform medical monitoring from reactive to proactive care.
My research advances the convergence of robotics and healthcare through intelligent sensing systems that enhance human-robot interaction and medical diagnostics. I have developed multimodal sensory electronic skin that enables synchronized haptic interfaces for augmented human-robot interaction, while artificial compound eye technology provides robots with advanced spatiotemporal perception and cognition capabilities in three-dimensional space. In healthcare applications, I have created integrated biosensors with near-sensor AI algorithms for rapid virus detection and developed adaptive multimodal biomedical sensing systems for early recognition of neurodegenerative disorders, particularly Parkinson's disease. These innovations demonstrate how my robotics-inspired sensing approach can transform medical monitoring from reactive to proactive care.
On-device AI using Analog/Digital signal computing
My pioneering work in neuromorphic computing focuses on developing energy-efficient hardware architectures that perform AI computations directly at the sensor level. This edge intelligence approach through in-sensor and near-sensor computing addresses critical challenges in the artificial intelligence of things by enabling real-time processing while preserving data privacy and reducing system latency. For AI computing on hardware, my approach involves both analog and digital computing. For analog computing, I have designed ternary charge-trap transistors that enable quantized neural networks with significantly reduced computational overhead, and oxide-based memristive crossbar arrays that perform in-memory computing and Multiply-accumulate (MAC) operation, eliminating the traditional bottleneck between processing and memory units. For digital computing, I have integrated a microprocessor, embedding neural network algorithms optimized for the resource-limited harware. This heterogeneous integration of analog and digital computing with hardware-software co-designed approach enables on-device AI for AIoT.
My pioneering work in neuromorphic computing focuses on developing energy-efficient hardware architectures that perform AI computations directly at the sensor level. This edge intelligence approach through in-sensor and near-sensor computing addresses critical challenges in the artificial intelligence of things by enabling real-time processing while preserving data privacy and reducing system latency. For AI computing on hardware, my approach involves both analog and digital computing. For analog computing, I have designed ternary charge-trap transistors that enable quantized neural networks with significantly reduced computational overhead, and oxide-based memristive crossbar arrays that perform in-memory computing and Multiply-accumulate (MAC) operation, eliminating the traditional bottleneck between processing and memory units. For digital computing, I have integrated a microprocessor, embedding neural network algorithms optimized for the resource-limited harware. This heterogeneous integration of analog and digital computing with hardware-software co-designed approach enables on-device AI for AIoT.
My pioneering work in neuromorphic computing focuses on developing energy-efficient hardware architectures that perform AI computations directly at the sensor level. This edge intelligence approach through in-sensor and near-sensor computing addresses critical challenges in the artificial intelligence of things by enabling real-time processing while preserving data privacy and reducing system latency. For AI computing on hardware, my approach involves both analog and digital computing. For analog computing, I have designed ternary charge-trap transistors that enable quantized neural networks with significantly reduced computational overhead, and oxide-based memristive crossbar arrays that perform in-memory computing and Multiply-accumulate (MAC) operation, eliminating the traditional bottleneck between processing and memory units. For digital computing, I have integrated a microprocessor, embedding neural network algorithms optimized for the resource-limited harware. This heterogeneous integration of analog and digital computing with hardware-software co-designed approach enables on-device AI for AIoT.
Advanced Semiconductor Growth and 2D Materials
I have contributed significantly to next-generation semiconductor manufacturing through remote epitaxy and two-dimensional materials integration. My research on high-throughput manufacturing of epitaxial membranes using 2D materials-based layer transfer processes enables the production of multiple single-crystalline semiconductor membranes from a single wafer. I have developed expertise in epitaxial growth of III-V and III-nitride materials via molecular beam epitaxy, including gallium nitride and hexagonal boron nitride on various substrates. My work on graphene-assisted epitaxy demonstrates how 2D materials can serve as universal platforms for defect reduction and strain relaxation in heteroepitaxial growth, opening pathways for cost-effective production of high-quality compound semiconductors.
I have contributed significantly to next-generation semiconductor manufacturing through remote epitaxy and two-dimensional materials integration. My research on high-throughput manufacturing of epitaxial membranes using 2D materials-based layer transfer processes enables the production of multiple single-crystalline semiconductor membranes from a single wafer. I have developed expertise in epitaxial growth of III-V and III-nitride materials via molecular beam epitaxy, including gallium nitride and hexagonal boron nitride on various substrates. My work on graphene-assisted epitaxy demonstrates how 2D materials can serve as universal platforms for defect reduction and strain relaxation in heteroepitaxial growth, opening pathways for cost-effective production of high-quality compound semiconductors.
I have contributed significantly to next-generation semiconductor manufacturing through remote epitaxy and two-dimensional materials integration. My research on high-throughput manufacturing of epitaxial membranes using 2D materials-based layer transfer processes enables the production of multiple single-crystalline semiconductor membranes from a single wafer. I have developed expertise in epitaxial growth of III-V and III-nitride materials via molecular beam epitaxy, including gallium nitride and hexagonal boron nitride on various substrates. My work on graphene-assisted epitaxy demonstrates how 2D materials can serve as universal platforms for defect reduction and strain relaxation in heteroepitaxial growth, opening pathways for cost-effective production of high-quality compound semiconductors.
Heterointegration and Layer Transfer Technologies
My expertise in heterogeneous integration encompasses advanced packaging techniques and layer transfer technologies that enable the combination of dissimilar materials for enhanced device performance. My research on remote epitaxy and freestanding wide bandgap semiconductor membrane technology addresses critical challenges in scaling and cost reduction for industrial applications. I have developed methodologies for integrating various functional materials including III-V compounds, oxides, and 2D materials onto diverse substrates, enabling applications from power electronics to flexible devices. This work on membrane-based technologies facilitates efficient thermal management and allows for the reuse of expensive substrates, significantly reducing manufacturing costs while maintaining high material quality.
My expertise in heterogeneous integration encompasses advanced packaging techniques and layer transfer technologies that enable the combination of dissimilar materials for enhanced device performance. My research on remote epitaxy and freestanding wide bandgap semiconductor membrane technology addresses critical challenges in scaling and cost reduction for industrial applications. I have developed methodologies for integrating various functional materials including III-V compounds, oxides, and 2D materials onto diverse substrates, enabling applications from power electronics to flexible devices. This work on membrane-based technologies facilitates efficient thermal management and allows for the reuse of expensive substrates, significantly reducing manufacturing costs while maintaining high material quality.
My expertise in heterogeneous integration encompasses advanced packaging techniques and layer transfer technologies that enable the combination of dissimilar materials for enhanced device performance. My research on remote epitaxy and freestanding wide bandgap semiconductor membrane technology addresses critical challenges in scaling and cost reduction for industrial applications. I have developed methodologies for integrating various functional materials including III-V compounds, oxides, and 2D materials onto diverse substrates, enabling applications from power electronics to flexible devices. This work on membrane-based technologies facilitates efficient thermal management and allows for the reuse of expensive substrates, significantly reducing manufacturing costs while maintaining high material quality.
Wearable Multimodal Sensors
My research in wearable sensing technology focuses on developing flexible, multimodal sensor networks that can monitor diverse physiological and environmental parameters simultaneously. I have created a network of artificial olfactory receptors that enables spatiotemporal monitoring of toxic gases, while my integrated pressure sensor systems combined with neuromorphic computing provide real-time gait analysis for health monitoring applications. I have fabricated piezoelectric pressure sensors, triboelectric devices for tremor detection, and integrated sensor arrays on flexible substrates that maintain functionality under mechanical deformation. These multimodal sensing platforms incorporate on-device AI processing capabilities, enabling comprehensive health monitoring while ensuring data privacy and reducing the need for external computational resources.
My research in wearable sensing technology focuses on developing flexible, multimodal sensor networks that can monitor diverse physiological and environmental parameters simultaneously. I have created a network of artificial olfactory receptors that enables spatiotemporal monitoring of toxic gases, while my integrated pressure sensor systems combined with neuromorphic computing provide real-time gait analysis for health monitoring applications. I have fabricated piezoelectric pressure sensors, triboelectric devices for tremor detection, and integrated sensor arrays on flexible substrates that maintain functionality under mechanical deformation. These multimodal sensing platforms incorporate on-device AI processing capabilities, enabling comprehensive health monitoring while ensuring data privacy and reducing the need for external computational resources.
My research in wearable sensing technology focuses on developing flexible, multimodal sensor networks that can monitor diverse physiological and environmental parameters simultaneously. I have created a network of artificial olfactory receptors that enables spatiotemporal monitoring of toxic gases, while my integrated pressure sensor systems combined with neuromorphic computing provide real-time gait analysis for health monitoring applications. I have fabricated piezoelectric pressure sensors, triboelectric devices for tremor detection, and integrated sensor arrays on flexible substrates that maintain functionality under mechanical deformation. These multimodal sensing platforms incorporate on-device AI processing capabilities, enabling comprehensive health monitoring while ensuring data privacy and reducing the need for external computational resources.
