Current Research Projects
Millimeter-wave for Multi-user Extended Reality
| The project investigates cross-layer techniques that can enable a high-quality immersive experience through extended reality (AR/VR/MR) over high-speed, unreliable mmWave wireless networks. |
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- Project Website; Collaborator: Bo Han (Mason)
- Selected Publications: SenSys '22 , Networks '22 , HotNets '22
Efficient Millimeter-wave networking through coordination
| The main goal of the project is to develop a new class of techniques that exploits network level coordination between access points in mmWave WiFi to reduce beamforming overhead, improve coverage and blockage resilience. |
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- Project Website; Collaborator: Zizhan Zheng (Tulane)
- Selected Publications: Sigmetrics '23 , HotMobile '22 , Milcom '21 , ICCCN '19' , MobiHoc '18
Securing RIS-assisted NextG millimeter-wave communication
| The focus of the project is to secure RIS-assisted mmWave networks from adversarial transmissions through development of authentication and physical layer key generation techniques. |
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- Project Website; Collaborator: Kai Zeng, Vijay Shah (Mason), Jacek Kibilda (VT)
- Selected Publications: Coming soon..
Millimeter-wave and wearable sensing
| The project focuses on how mmWave radars and WiFi devices can be leveraged for creating a low-cost sensing modality through infrastructure reuse with application in sign language recognition for deaf and hard-of-hearing. |
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- Project Website; Collaborator: Huzefa Rangwala, Jana Kosecka (Mason), Kenneth DeHaan (Gallaudet)
- Selected Publications: Ubicomp '23 , Secon '20 , Ubicomp '20 , S&P '22 , Infocom '22
Millimeter-wave IoTs through backscattering
| The major goal of this project is to create high-speed, low-power mmWave IoT devices through backscattering and devise protocols for their seamless integration for mmWave networking and sensing. |
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- Project Website; Collaborator: Song Min Kim (KAIST)
- Selected Publications: NSDI '24 , Mobisys '22 , WinTech '21
Efficient and accurate wireless propagation prediction
| Through this project, we are aiming to develop a novel framework for RF propagation prediction which embeds the environment information (e.g., 3D maps of buildings) directly into the ray tracing process through the use of deep learning. |
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- Project Website; Collaborator: AT&T Labs
- Selected Publications: Coming soon..
Millimeter-wave networking for high-speed CPS
| The project aims at developing novel, custom-tailored solutions for challenges associated with mmWave networks operating in cyber physical systems such as vehicles, UAVs, and UGVs with high-speed mobility and transcience. |
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- Project Website; Collaborator: Robert Ulman (ARL), Robert Simon (Mason), Prasant Mohapatra (UC Davis)
- Selected Publications: MobiCom '23