Towards Wireless Precision Sensing in IoT for Human Interaction, Healthcare, and Beyond

Speaker: Chenhan XU
         Department of Computer Science and Engineering
         University at Buffalo, the State University of New York (SUNY)

Title:  "Towards Wireless Precision Sensing in IoT for Human Interaction,
        Healthcare, and Beyond"

Date:   Tuesday, 13 December 2022

Time:   10:00am - 11:00am


Join Zoom Link:
https://hkust.zoom.us/j/465698645?pwd=aVRaNWs2RHNFcXpnWGlkR05wTTk3UT09

Meeting ID: 465-698-645
Passcode: 20222023


Abstract:

Nowadays, IoT devices are encroaching on every environment of our lives,
including but not limited to homes, vehicles, and offices. However, due to
the complexity of human activities, unavoidable variance in signal
scaling, and privacy-preserving requirements, only limited human
information can be cognized by the IoT environment, leading to a great gap
between IoT intelligence and human demands. In this talk, I will introduce
how we build sensing and computing systems that aim for precise, secure,
intelligent, and broad-spectrum human-computer interaction (HCI). In
particular, I will present our work that is the first to exploit
high-precision millimeter wave direct sensing of the human vocal system to
solve acoustic noise problems on conventional voice sensing for decades,
which is a fundamental refactor of voice sensing and enables new voice
computing applications. I will also present our work on a next-generation
voice-user interface that enables pervasive heart-sensing functions. I
will conclude my talk with future directions in IoT systems for human.


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Biography:

Chenhan Xu is a final-year Ph.D. candidate in the Department of Computer
Science and Engineering at the University at Buffalo, the State University
of New York. He is working in the Embedded Sensing and Computing Lab under
the supervision of Prof. Wenyao Xu. Chenhan received B.Eng. in Network
Engineering (2017) from Nanjing University of Posts and
Telecommunications, China. His research interests include the Internet of
Things, Cybersecurity, Physiological Science, and Smart Health. The
central theme of his research is to model, design, build, and evaluate
end-to-end sensing and computing systems that aim for precise,
broad-spectrum, intelligent, and secure human-computer interaction (HCI)
and personalized healthcare within the Internet-of-Things context. Chenhan
has published more than 30 research papers in high-impact venues for
mobile computing (e.g., MobiCom, MobiSys, SenSys), human-computer
interaction (UbiComp), smart health/bioinformatics (e.g., ICHI, CHASE),
and security (NDSS). He is the recipient of the Best Student Paper Award
at ICHI'22 and Best Paper Awards at MobiSys'20 and SenSys'19.