TaskSense introduces a sensor language that automatically translates the capabilities and data dependencies of sensor systems into vocabularies and
grammar rules that can be understood by LLMs. It then interprets
user intentions into executable task plans for sensor systems using this sensor language in combination with LLMs.
SHADE-AD, a Large Language Model (LLM) framework for Synthesizing Human Activity Datasets Embedded with AD features. Leveraging both public datasets and our own collected data from 99 AD patients, SHADE-AD synthesizes human activity videos that specifically represent AD-related behaviors.
The ACM Fellow Program initiated in 1993. It recognizes the top 1% of ACM members for their outstanding accomplishments in technology and/or outstanding service to ACM and the larger computing community. In 2024, 55 members have been elected as ACM fellows for transformative contributions to computing science and technology.
The ACM Fellow Program initiated in 1993. It recognizes the top 1% of ACM members for their outstanding accomplishments in technology and/or outstanding service to ACM and the larger computing community. In 2024, 55 members have been elected as ACM fellows for transformative contributions to computing science and technology.
Congratulations to Di for receiving the Best Paper Honorable Mention Award at SenSys 2025!
Argus, a wearable add-on system based
on stripped-down (i.e., compact, lightweight, low-power, limitedcapability) mmWave radars. It is the first to achieve egocentric human mesh reconstruction in a multi-view manner. Compared with
conventional frontal-view mmWave sensing solutions, it addresses
several pain points, such as restricted sensing range, occlusion, and
the multipath effect caused by surroundings.
Our research projects, An Intelligent LiDAR with Adaptive Focus and Sonar-based Underwater Human Activity Monitoring System, received two gold medals at the 50th International Exhibition…
The ACM Fellow Program initiated in 1993. It recognizes the top 1% of ACM members for their outstanding accomplishments in technology and/or outstanding service to ACM and the larger computing community. In 2024, 55 members have been elected as ACM fellows for transformative contributions to computing science and technology.
Asteroid, a distributed edge training system that breaks the resource walls across heterogeneous edge devices for efficient model training acceleration. Asteroid adopts a hybrid pipeline parallelism to orchestrate distributed training, along with a judicious parallelism planning for maximizing throughput undercertain resource constraints.