77 citations · 109 across the 18 of their papers we have counts for
19 papers
NoisePQC++: A Unified NIST-Compliant PQC and Hybrid-PQC Implementation of the Noise Protocol
Nadeem Ahmed, Aryya Gangopadhyay, Lei Zhang
The threat of quantum computers to classical public-key cryptography has created an urgent need to evolve secure communication protocols with post-quantum cryptographic (PQC) primi…
Hilbert-Augmented Reinforcement Learning for Scalable Multi-Robot Coverage and Exploration
Tamil Selvan Gurunathan, Aryya Gangopadhyay
We present a coverage framework that integrates Hilbert space-filling priors into decentralized multi-robot learning and execution. We augment DQN and PPO with Hilbert-based spatia…
A Survey of Post-Quantum Cryptography Support in Cryptographic Libraries
Nadeem Ahmed, Lei Zhang, Aryya Gangopadhyay
The rapid advancement of quantum computing poses a significant threat to modern cryptographic systems, necessitating the transition to Post-Quantum Cryptography (PQC). This study e…
Integrating Frequency-Domain Representations with Low-Rank Adaptation in Vision-Language Models
Md Azim Khan, Aryya Gangopadhyay, Jianwu Wang +1
Situational awareness applications rely heavily on real-time processing of visual and textual data to provide actionable insights. Vision language models (VLMs) have become essenti…
A Lightweight Plug-in Module for Introducing Post-Quantum Cryptography in Higher Education: An Experience Report
Ainaz Jamshidi, Khushdeep Kaur, Karen Chen +2
Post-quantum cryptography (PQC) is increasingly important for computing education, yet integrating it into existing curricula is challenging because it draws on programming, mathem…
TinyVQA: Compact Multimodal Deep Neural Network for Visual Question Answering on Resource-Constrained Devices
Hasib-Al Rashid, Argho Sarkar, Aryya Gangopadhyay +2
Traditional machine learning models often require powerful hardware, making them unsuitable for deployment on resource-limited devices. Tiny Machine Learning (tinyML) has emerged a…
Skip-WaveNet: A Wavelet based Multi-scale Architecture to Trace Snow Layers in Radar Echograms
Debvrat Varshney, Masoud Yari, Oluwanisola Ibikunle +4
Airborne radar sensors capture the profile of snow layers present on top of an ice sheet. Accurate tracking of these layers is essential to calculate their thicknesses, which are r…
Mixed Precision Quantization to Tackle Gradient Leakage Attacks in Federated Learning
Pretom Roy Ovi, Emon Dey, Nirmalya Roy +1
Federated Learning (FL) enables collaborative model building among a large number of participants without the need for explicit data sharing. But this approach shows vulnerabilitie…
TagTeam: Towards Wearable-Assisted, Implicit Guidance for Human--Drone Teams
Kasthuri Jayarajah, Aryya Gangopadhyay, Nicholas Waytowich
The availability of sensor-rich smart wearables and tiny, yet capable, unmanned vehicles such as nano quadcopters, opens up opportunities for a novel class of highly interactive, a…
An Edge-Cloud Integrated Framework for Flexible and Dynamic Stream Analytics
Xin Wang, Azim Khan, Jianwu Wang +3
With the popularity of Internet of Things (IoT), edge computing and cloud computing, more and more stream analytics applications are being developed including real-time trend predi…
TinyMNet: A Flexible System Algorithm Co-designed Multimodal Learning Framework for Tiny Devices
Hasib-Al Rashid, Pretom Roy Ovi, Carl Busart +2
With the emergence of Artificial Intelligence (AI), new attention has been given to implement AI algorithms on resource constrained tiny devices to expand the application domain of…
Reproducible and Portable Big Data Analytics in the Cloud
Xin Wang, Pei Guo, Xingyan Li +4
Cloud computing has become a major approach to help reproduce computational experiments. Yet there are still two main difficulties in reproducing batch based big data analytics (in…
CCS-GAN: COVID-19 CT-scan classification with very few positive training images
Sumeet Menon, Jayalakshmi Mangalagiri, Josh Galita +7
We present a novel algorithm that is able to classify COVID-19 pneumonia from CT Scan slices using a very small sample of training images exhibiting COVID-19 pneumonia in tandem wi…
Toward Generating Synthetic CT Volumes using a 3D-Conditional Generative Adversarial Network
Jayalakshmi Mangalagiri, David Chapman, Aryya Gangopadhyay +7
We present a novel conditional Generative Adversarial Network (cGAN) architecture that is capable of generating 3D Computed Tomography scans in voxels from noisy and/or pixelated a…
Generating Realistic COVID19 X-rays with a Mean Teacher + Transfer Learning GAN
Sumeet Menon, Joshua Galita, David Chapman +7
COVID-19 is a novel infectious disease responsible for over 800K deaths worldwide as of August 2020. The need for rapid testing is a high priority and alternative testing strategie…
AutoCogniSys: IoT Assisted Context-Aware Automatic Cognitive Health Assessment
Mohammad Arif Ul Alam, Nirmalya Roy, Sarah Holmes +2
Cognitive impairment has become epidemic in older adult population. The recent advent of tiny wearable and ambient devices, a.k.a Internet of Things (IoT) provides ample platforms…
Localized Flood DetectionWith Minimal Labeled Social Media Data Using Transfer Learning
Neha Singh, Nirmalya Roy, Aryya Gangopadhyay
Social media generates an enormous amount of data on a daily basis but it is very challenging to effectively utilize the data without annotating or labeling it according to the tar…
FLATM: A Fuzzy Logic Approach Topic Model for Medical Documents
Amir Karami, Aryya Gangopadhyay, Bin Zhou +1
One of the challenges for text analysis in medical domains is analyzing large-scale medical documents. As a consequence, finding relevant documents has become more difficult. One o…
Fuzzy Approach Topic Discovery in Health and Medical Corpora
Amir Karami, Aryya Gangopadhyay, Bin Zhou +1
The majority of medical documents and electronic health records (EHRs) are in text format that poses a challenge for data processing and finding relevant documents. Looking for way…