% Official BibTeX citations for Tanvir Ahmed's publications.
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@inproceedings{10.3217/99wp-7p13,
author = {Gao, Yixuan and Ahmed, Tanvir and Mohammed, Mikhail and Cheng, Zhongqi and Nandakumar, Rajalakshmi},
title = {Feasibility of Radio Frequency Based Wireless Sensing of Lead Contamination in Soil},
year = {2024},
publisher = {International Conference on Embedded Wireless Systems and Networks (EWSN)},
url = {https://doi.org/10.3217/99wp-7p13},
doi = {10.3217/99wp-7p13},
abstract = {Widespread Pb (lead) contamination of urban soil significantly impacts food safety and public health and hinders city greening efforts. However, most existing technologies for measuring Pb are labor-intensive and costly. In this study, we propose SoilScanner, a radio frequency-based wireless system that can detect Pb in soils. This is based on our discovery that the propagation of different frequency band radio signals is affected differently by different salts such as NaCl and Pb(NO3)2 in the soil. In a controlled experiment, manually adding NaCl and Pb(NO3)2 in clean soil, we demonstrated that different salts reflected signals at different frequencies in distinct patterns. In addition, we confirmed the finding using uncontrolled field samples with a machine learning model. Our experiment results show that SoilScanner can classify soil samples into low-Pb and high-Pb categories (threshold at 200 ppm) with an accuracy of 72\%, with no sample with >500 ppm of Pb being misclassified. The results of this study show that it is feasible to build portable and affordable Pb detection and screening devices based on wireless technology.},
booktitle = {Proceedings of the 2024 International Conference on Embedded Wireless Systems and Networks},
pages = {193–204},
numpages = {12},
keywords = {Sensing Application, Urban Health, Soil Lead Contamination, Signal Processing, Machine Learning},
location = {Abu Dhabi, UAE},
series = {EWSN '24}
}

@inproceedings{10.1145/3708468.3711880,
author = {Gao, Yixuan and Ahmed, Tanvir and Chang, Zekun and Roumen, Thijs and Nandakumar, Rajalakshmi},
title = {VitalHide: Enabling Privacy-Aware Wireless Sensing of Vital Signs},
year = {2025},
isbn = {9798400714030},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/3708468.3711880},
doi = {10.1145/3708468.3711880},
abstract = {Wireless sensing technologies leveraging the acoustic and RF sensors in smart devices have advanced to enable accurate contactless monitoring of vital signs such as breathing and heartbeat. Wireless signal monitoring can enable important health applications, such as determining emotional states, detecting critical health conditions, and providing suitable interventions. While offering non-invasiveness and privacy advantages over wearables and cameras, these technologies pose serious privacy risks. The improved sensing accuracy allows any unauthorized sensor to detect sensitive health data without consent. This paper proposes VitalHide, a novel approach to protect vital signs from unauthorized sensing while still enabling wireless sensing for authorized devices. The key idea of VitalHide is to obfuscate the user's vital signs by generating a deceiving vital sign motion using a wearable mechanical device. The obfuscated signal can then only be decoded at authorized devices, while unauthorized devices receive deceiving vital signs. We show the feasibility of VitalHide by generating motion using a vibration sensor and shape memory alloy (SMA)-based smart textile, and the successful decoding of the obfuscated vital sign signal at the authorized receiver. This work advances privacy-preserving wireless sensing by securing personal health information against unauthorized access without affecting the utility of authorized devices.},
booktitle = {Proceedings of the 26th International Workshop on Mobile Computing Systems and Applications},
pages = {37–42},
numpages = {6},
keywords = {Privacy, Smart Textile, Wireless Sensing},
location = {La Quinta, CA, USA},
series = {HotMobile '25}
}

% Pre-publication metadata from the ACM copyright citation; add page numbers and ISBN when available.
@inproceedings{10.1145/3795866.3844486,
author = {Ahmed, Tanvir and Gao, Yixuan and Armouti, Adnan and Nandakumar, Rajalakshmi},
title = {{mmFHE}: {mmWave} Sensing with End-to-End Fully Homomorphic Encryption},
year = {2026},
month = oct,
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/3795866.3844486},
doi = {10.1145/3795866.3844486},
booktitle = {The 32nd Annual International Conference on Mobile Computing and Networking},
numpages = {17},
location = {Austin, TX, USA},
series = {MobiCom '26}
}

@article{10.1039/d2na00571a,
author = {Himel, Mehedi Hasan and Sikder, Bejoy and Ahmed, Tanvir and Choudhury, Sajid Muhaimin},
title = {Biomimicry in nanotechnology: a comprehensive review},
journal = {Nanoscale Advances},
volume = {5},
number = {3},
pages = {596-614},
year = {2023},
month = {02},
abstract = { Biomimicry has been utilized in many branches of science and engineering to develop devices for enhanced and better performance. The application of nanotechnology has made life easier in modern times. It has offered a way to manipulate matter and systems at the atomic level. As a result, the miniaturization of numerous devices has been possible. Of late, the integration of biomimicry with nanotechnology has shown promising results in the fields of medicine, robotics, sensors, photonics, etc. Biomimicry in nanotechnology has provided eco-friendly and green solutions to the energy problem and in textiles. This is a new research area that needs to be explored more thoroughly. This review illustrates the progress and innovations made in the field of nanotechnology with the integration of biomimicry. },
issn = {2516-0230},
doi = {10.1039/d2na00571a},
url = {https://doi.org/10.1039/d2na00571a},
eprint = {https://pubs.rsc.org/na/article-pdf/5/3/596/8561053/d2na00571a.pdf}
}


@INPROCEEDINGS{10089141,
  author={Ahmed, Tanvir and Nakib, Mohtasim and Haque, Mohammad Ariful and Miah, Md Messal Monem},
  booktitle={2022 12th International Conference on Electrical and Computer Engineering (ICECE)},
  title={COVID-19 Identification From Lung CT Scans in a Low-Resource Setting Using a Regularized 3D Convolutional Neural Network},
  year={2022},
  volume={},
  number={},
  pages={248-251},
  keywords={COVID-19;Solid modeling;Three-dimensional displays;Pandemics;Computed tomography;Lung;Medical services;COVID-19;lung CT;mutation;3D CNN},
  doi={10.1109/ICECE57408.2022.10089141}}