Professor Receives Prestigious Paper Award at IEEE Conference
In June, the Institute of Electrical and Electronics Engineering (IEEE) Conference on Distributed Computing Systems (ICDCS) awarded Yingying Chen, Department of Electrical and Computer Engineering Distinguished Professor and Chair, and her team its Distinguished Paper award. This recognition, according to Chen, is her research group's ninth best paper award.
The highly selective IEEE ICDCS—with a less than 20% acceptance rate for the 2026 conference—recognized the groundbreaking research presented by Chen and her Temple University collaborators on BeamGes—the first motion-resilient hand gesture recognition system for smartphones.
Chen explains how "extensive experiments over six months across various environments, devices, and motion conditions demonstrated that BeamGes can achieve 89.2% accuracy, indicating that reliable, touchless gesture sensing is possible on commodity smartphones that are industry-standardized across brands."
For Chen, the Distinguished Paper Award is meaningful for her, as well as for her research team, which includes her PhD student Zejun Xu, and Temple PhD student Zijie Tang and advisor Yan Wang.
"I've done pioneering work in wireless sensing for activity recognition, mobile sensing, and human-mobile-device interaction since their infancy," she says.
"Over the years, we have explored how wireless signals from everyday devices can be used to understand human activities in practical and privacy-conscious ways. BeamGes continues that effort and demonstrates our sustained commitment and strength in this area."
Controlling Smartphones without Touching the Screen
While this award-winning work shares the same goal as Chen's prior ground-breaking facial recognition work of making human-device interaction more natural, secure, and effortless, the benefit of BeamGes, according to Chen, is that smartphone users can control their phones without touching the screens.
"For example, they can control music or video and navigate simple menus with hand gestures, which can be especially useful when touching the screen while cooking, exercising, driving, or wearing gloves is inconvenient," Chen notes.
BeamGes, she remarks, can make mobile interaction more natural and accessible on other low-cost WiFi-enabled devices, such as wearables and smart appliances, when typing or tapping can be impossible without a touchscreen. "In addition, the wireless signal-based recognition technology can potentially provide second-factor user authentication with a digital or gesture-based passcode on mobile devices.
A Promising Technique
Ultimately, hand gesture recognition and facial recognition would be complementary, as facial recognition verifies the user's identity, while hand gestures help the device capture what the user wants it to do.
"I believe BeamGes has market potential, although additional work would be needed before commercialization," Chen says. "It's a promising technique for mobile interaction, smart-home control, wearable devices, and extended reality, or XRs, applications."
