Efficient Computing for Machine Learning at the Edge
We make machine learning computing faster and more efficient for embedded applications with scarce compute resources. We develop various design-time and run-time techniques in circuit, architecture, and algorithm levels, such as neural network model reduction and energy-quality scalable computing.
Beyond Approximate Computing: Enabling Full-System Energy-Quality Scalability in Embedded Systems
National Science Foundation
NSF AI Institute for Edge Computing Leveraging Next Generation Networks
National Science Foundation
Enabling a Global Spectrum Observatory through Mobile, Wide-band Spectrum Sensing Kits and a Software Ecosystem
National Science Foundation
SynthNet (ASP-DAC 2022)
A high-throughput yet energy-efficient combinational logic neural network
SECO (ISLPED 2019)
A scalable accuracy approximate exponential function via cross-level optimization
SAADI (ASP-DAC 2019)
A scalable accuracy approximate divider for dynamic energy-quality scaling
Usable Security and Privacy for Mobile and Embedded Systems
We make the Internet-of-Things and human-computer interaction (VR/AR) more trustworthy through usability-aware security and privacy. We develop techniques for ensuring a high level of security and privacy that are easy to understand and use for the users.
Sponsors
National Science Foundation, Intel Corporation, Meta (Facebook)
Kaleido (USENIX Security 2021)
Real-time privacy control for eye-tracking systems
VoltKey (UbiComp 2019)
Continuous secret key generation based on power line noise for zero-involvement pairing and authentication
CamPUF (DAC 2018)
Physically unclonable function based on CMOS image sensor fixed pattern noise
Embedded Systems Applications
We solve societal problems in areas such as healthcare, agriculture, and environment using embedded computing and networking technologies. We utilize advanced Internet-of-Things and machine learning techniques for monitoring, data analytics, and decision-making.
Mitigating Heat Stress in Dairy Cattle using a Physiological Sensing-Behavior Analysis-Microclimate Control Loop
USDA National Institute of Food and Agriculture
CompAg 2020
Using implantable biosensors and wearable scanners to monitor dairy cattle’s core body temperature in real-time
TMSCS 2019
Design and management of battery-supercapacitor hybrid electrical energy storage systems for regulation services
TeleProbe (ISLPED 2016)
Zero-power contactless probing for implantable medical devices
Research Sponsors
We appreciate the generous sponsors who make our research possible