
GitHub: github.com/PANSLAB
The number of everyday smart devices (e.g., Nest, Notion, Samsung SmartThings) is projected to grow to the billions in the coming decade. The Cyber-Physical Systems or Internet of Things systems that consist of these devices obtain human information for various smart applications (e.g., elderly care, patient monitoring, etc.). Due to the complexity of the physical world, data acquisition quality and sensing data distributions can change significantly under different sensing conditions, resulting in requiring more resources to achieve accurate information inference.
We aim to Sense for Less to make CPS/IoT systems more pervasive. From the system perspective, our research focuses on autonomous-assessing, configuring, and adapting heterogeneous cyber-physical sensing systems for accurate non-intrusive human information inference. From the data perspective, our research addresses the challenges of limited labeled data by combining physical and data-driven knowledge to model the change.
The University of California, Merced is located between Silicon Valley and the beautiful Yosemite National Park, allowing us to work closely with our industrial collaborators.
2022 SenSys/BuildSys @ Boston


2020 Spring Cyber-Physical Sensing Systems Research Retreat
@ Yosemite National Park
