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COLLOQUIUM: Elahe Soltanaghai, "Perceiving The World with Pervasive Wireless Infrastructures"

Event Type
Seminar/Symposium
Sponsor
Illinois Computer Science
Location
https://mediaspace.illinois.edu/media/t/1_oi2t5fs7
Date
Sep 29, 2021   3:30 pm  
Views
146
Originating Calendar
Computer Science Colloquium Series

Link to Talk Video: https://mediaspace.illinois.edu/media/t/1_oi2t5fs7

Abstract: Emerging applications such as smart cities, autonomous vehicles, and mixed reality rely on embedded systems that are engaging with the physical environment through sensors. Building upon this connection, my vision is to advance Omnipresent Sensing by harnessing the wireless infrastructure in and around buildings and cities to act as a non-intrusive sensing platform. This is possible by innovating at the crossroads of two recent trends in mobile computing: (1) Wireless technologies such as Millimeter-wave (mmWave) and Massive MIMO systems can now support higher bandwidth for communication and improved resolution for RF sensing applications. (2) Advancements in CPUs and RF front-ends are making it easier to develop software-defined sensing and communication systems. This is affording edge devices the ability to do more advanced signal processing and machine learning.   

In this talk, I will focus on how to design an RF-equivalent of optical retro-reflectors and use them as fiducial markers in autonomous vehicles, robotics, and mixed reality applications. I will then discuss how nuances from the environment itself can be leveraged to improve sensing quality in the context of human sensing, object tracking, and indoor localization. I will conclude this talk with a roadmap of combining radar-style RF sensors and wireless communication links for the wireless embedded systems of the future. 

Elahe

Bio: Elahe Soltanaghai is an assistant professor of Computer Science at the University of Illinois Urbana-Champaign. Her research builds a foundation for joint communication and sensing in wireless embedded systems of the future by applying signal processing and machine learning techniques to low-level RF signals. Previously, she was a postdoctoral researcher at Carnegie Mellon University in CyLab. She received her PhD in Computer Science from University of Virginia. Reflecting the multidisciplinary nature of her research, her work has been published in premier conferences and journals in the areas of mobile and ubiquitous computing, wireless networks, and energy and infrastructure. She has been named one of the 10 Rising Star Women in Networking and Communications in 2021. She is also the recipient of 2020 ACM SIGMOBILE Dissertation Award and 2019 EECS Rising Stars

 

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Part of the Illinois Computer Science Speakers Series. Faculty Host: Robin Kravets

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