activity
20232025
most citedWireless Spectrum in Rural Farmlands: Status, Challenges and Opportunities

1 citations · 2 across the 6 of their papers we have counts for

collaborators

6 papers

eess.SP2025

ReVeal-MT: A Physics-Informed Neural Network for Multi-Transmitter Radio Environment Mapping

Mukaram Shahid, Kunal Das, Hadia Ushaq +7

Accurately mapping the radio environment (e.g., identifying wireless signal strength at specific frequency bands and geographic locations) is crucial for efficient spectrum sharing…

eess.SP2025★ 1 cited

ReVeal: A Physics-Informed Neural Network for High-Fidelity Radio Environment Mapping

Mukaram Shahid, Kunal Das, Hadia Ushaq +7

Accurately mapping the radio environment (e.g., identifying wireless signal strength at specific frequency bands and geographic locations) is crucial for efficient spectrum sharing…

cs.NI2024

Design and Implementation of ARA Wireless Living Lab for Rural Broadband and Applications

Taimoor Ul Islam, Joshua Ofori Boateng, Md Nadim +31

Addressing the broadband gap between rural and urban regions requires rural-focused wireless research and innovation. In the meantime, rural regions provide rich, diverse use cases…

cs.NI2024★ 1 cited

Wireless Spectrum in Rural Farmlands: Status, Challenges and Opportunities

Mukaram Shahid, Kunal Das, Taimoor Ul Islam +11

Due to factors such as low population density and expansive geographical distances, network deployment falls behind in rural regions, leading to a broadband divide. Wireless spectr…

cs.CR2024

Improving behavior based authentication against adversarial attack using XAI

Dong Qin, George Amariucai, Daji Qiao +1

In recent years, machine learning models, especially deep neural networks, have been widely used for classification tasks in the security domain. However, these models have been sh…

cs.LG2023

A Comprehensive and Reliable Feature Attribution Method: Double-sided Remove and Reconstruct (DoRaR)

Dong Qin, George Amariucai, Daji Qiao +2

The limited transparency of the inner decision-making mechanism in deep neural networks (DNN) and other machine learning (ML) models has hindered their application in several domai…