The number of everyday smart devices is projected to grow to billions in the coming decade. Our vision and mission are to make these intelligent networked devices more pervasive/ubiquitous and autonomous. Our research focuses on the acquisition, analysis, and augmentation of ambient information with limited/less resources.
[Pervasive Sensing] To effectively measure and monitor people's physical and behavioral health, continuous and user-imperceptible sensing is essential. We focus on contact-based sensing by converting everyday objects into sensors while preserving their regular usability (Surface as Sensors).
[Autonomous Adaptation] Due to the complexity of the physical world, data acquisition quality and sensing data distributions can change significantly under different sensing conditions, resulting in inaccurate detection and inference. We focus on autonomous assessing, configuring, and adapting heterogeneous sensing systems via cross-modal association using people as the shared context.
[Networked Intelligence] Data from multimodal networked devices provides complementary information. By exploring the complementary and correlation of multimodal sensor data with different spatial/mobile characteristics (static, semi-mobile, mobile), we establish efficient inference/model transfer schemes guided by the modality's spatial characteristics.
UC Merced is located between Silicon Valley and the beautiful Yosemite National Park
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