CSE PhD Graduates Dr. Qingyong HU and Dr. Yuxuan ZHOU (under the supervision of Prof. Qian Zhang) Awarded the ACM IMWUT Distinguished Paper Award at the UbiComp/ISWC

We are pleased to announce that our PhD graduates Dr. Qingyong HU and Dr. Yuxuan ZHOU (supervised by Prof. Qian ZHANG) received an ACM IMWUT Distinguished Paper Award at the ACM International Joint Conference on Pervasive and Ubiquitous Computing / International Symposium on Wearable Computing (UbiComp/ISWC), held in Espoo, Finland, in October.

UbiComp/ISWC is a premier interdisciplinary venue in which leading international researchers, designers, developers, and practitioners in the field present and discuss novel results in all aspects of ubiquitous, pervasive, and wearable computing. This award recognizes the enduring impact of their co-authored paper titled "Contactless Arterial Blood Pressure Waveform Monitoring with mmWave Radar."

Details about the UbiComp/ISWC

"Contactless Arterial Blood Pressure Waveform Monitoring with mmWave Radar"

Their paper was published in the Proceedings of the ACM on Interactive, Mobile, Wearable, and Ubiquitous Technologies (IMWUT). IMWUT assigns every year a Distinguished Paper Award to 3–4% of all papers published by the journal in the previous year (volume). This year, they selected — out of the 208 papers published in Volume 8 of PACM IMWUT — 8 papers that represent outstanding and exemplary contributions to our research community.

Current ABPW (arterial blood pressure waveform) monitoring methods require invasive procedures or continuous skin contact, which are inconvenient and unsatisfactory. In this work, we propose WaveBP, the first contactless ABPW monitoring system utilizing a commercial mmWave radar, driven by the understanding that cardiac information serves as an implicit bridge between mmWave signals and ABPW based on a hemodynamics analysis model. We propose a series of techniques that overcome the challenges of mapping mmWave signals to ABPW sequences, including a hybrid Transformer model with multi-resolution awareness and flexible personalization schemes, a novel radar-specific data augmentation based on beamforming to focus on cardiac information across different views, and a knowledge transfer framework to fuse extra knowledge from cardiac modalities without extra deployment overhead. As highlighted by the Best Paper Award selection committee: "This well-planned and well-executed study introduces a novel millimeter-wave radar and machine learning approach for non-invasive blood pressure monitoring. It tackles a challenging real-world problem with strong technical innovation, clear presentation, and promising impact on future healthcare sensing."

The awarded paper

Congratulations to the authors — Dr. HU, Dr. ZHOU, and Prof. ZHANG — on this remarkable accomplishment!

UbiComp/ISWC Award