I am a PhD candidate at Department of Electrical & Computer Engineering, University of Pittsburgh, advised by Dr. Wei Gao. I received my Bachelor’s Degree in Automation from the University of Science and Technology of China in 2019.

My research focuses on mobile sensing and AI for healthcare. I am also interested in applying AI techniques to robotics, IoT and other practical scenarios.

You can find my CV here.

Research Highlights

Smartphone-based Acoustic Sensing for Pulmonary Disease Evaluation

We developed a mobile health system that turns a commodity smartphone into a fully functional pulmonary examination device that measures the internal physiological conditions of human airways via acoustic sensing through mouth. Since 2020, our integrated AI and sensing systems, namely PTEase or Acoustic Waveform Respiratory Evaluation (AWARE), have been applied to and tested on more than 400 patients with various pulmonary diseases at the Children’s Hospital of Pittsburgh. Our work was published at SenSys’22 and MobiSys’23. We also published the dataset of human airway measurements, containing airway measurements of 382 human subjects with various pulmonary diseases and healthy control subjects collected over the past years.

Publications

• [MobiCom’24] Kai Huang, Xiangyu Yin, Tao Gu, and Wei Gao. 2024 (In press). Perceptual-Centric Image super-Resolution using Heterogeneous Processors on Mobile Devices. (Acceptance Rate: 19.1%)
• [MobiSys’23] Xiangyu Yin, Kai Huang, Erick Forno, Wei Chen, Heng Huang, and Wei Gao. 2023. PTEase: Objective Airway Examination for Pulmonary Telemedicine using Commodity Smartphones. In Proceedings of the 21st Annual International Conference on Mobile Systems, Applications and Services (MobiSys ‘23). Association for Computing Machinery, New York, NY, USA, 110–123. https://doi.org/10.1145/3581791.3596854 (Acceptance Rate: 20.7%)
• [CML-IOT’22/SenSys’22] Xiangyu Yin, Kai Huang, Erick Forno, Wei Chen, Heng Huang, and Wei Gao. 2023. Out-Clinic Pulmonary Disease Evaluation via Acoustic Sensing and Multi-Task Learning on Commodity Smartphones. In Proceedings of the 20th ACM Conference on Embedded Networked Sensor Systems (SenSys ‘22). Association for Computing Machinery, New York, NY, USA, 1182–1188. https://doi.org/10.1145/3560905.3568437 (Best Paper Award)

Education

• Ph.D., Electrical & Computer Engineering, Swanson School of Engineering, University of Pittsburgh (2019-Present)
• B.Eng., Automation, School of the Gifted Young (少年班学院), University of Science and Technology of China (2015-2019)