112 citations · 509 across the 43 of their papers we have counts for
35 papers · 1 filter
QIAP: A Quantum-Inspired Authentication Protocol with BB84-Based Channel Monitoring
Owais Ishtiaq Siddiqui, Nouhaila Innan, Hira Zaheer +1
Authentication in quantum-aware communication settings requires mechanisms that verify user legitimacy while also assessing whether the communication channel exhibits excessive dis…
QuantumChain: Blockchain-Backed Quantum Federated Learning for Financial Fraud Detection
Epameinondas Douros, Konstantinos Dalampekis, Nouhaila Innan +2
Financial fraud detection is challenged by decentralized data, severe class imbalance, and privacy constraints. This paper presents QuantumChain, a secure Quantum Federated Learnin…
MDQEC-QAS: Meta-Decoding for Quantum Error Correction with Hardware-Aware VQC Search and Confidence-Gated Recovery
Prashant Kumar Choudhary, Nouhaila Innan, Muhammad Shafique +1
We propose a unified meta-decoding framework for quantum error correction that learns syndrome-to-recovery mappings across multiple stabilizer codes and noise settings, without req…
FiD-QAE: A Fidelity-Driven Quantum Autoencoder for Credit Card Fraud Detection
Mansour El Alami, Adam Innan, Nouhaila Innan +2
Credit card fraud detection is a critical task in financial security, as fraudulent transactions are rare, highly imbalanced, and often resemble legitimate ones. A wide range of cl…
Graph-Based Bayesian Optimization for Quantum Circuit Architecture Search with Uncertainty Calibrated Surrogates
Prashant Kumar Choudhary, Nouhaila Innan, Muhammad Shafique +1
Quantum circuit design is a key bottleneck for practical quantum machine learning on complex, real-world data. We present an automated framework that discovers and refines variatio…
Benchmarking VQE Configurations: Architectures, Initializations, and Optimizers for Silicon Ground State Energy
Zakaria Boutakka, Nouhaila Innan, Muhammed Shafique +2
Quantum computing presents a promising path toward precise quantum chemical simulations, particularly for systems that challenge classical methods. This work investigates the perfo…
Evaluating Quantum Amplitude Estimation for Pricing Multi-Asset Basket Options
Muhammad Kashif, Shaf Khalid, Nouhaila Innan +2
Accurate and efficient pricing of multi-asset basket options poses a significant challenge, especially when dealing with complex real-world data. In this work, we investigate the r…
RobQFL: Robust Quantum Federated Learning in Adversarial Environment
Walid El Maouaki, Nouhaila Innan, Alberto Marchisio +3
Quantum Federated Learning (QFL) merges privacy-preserving federation with quantum computing gains, yet its resilience to adversarial noise is unknown. We first show that QFL is as…
CircuitHunt: Automated Quantum Circuit Screening for Superior Credit-Card Fraud Detection
Nouhaila Innan, Akshat Singh, Muhammad Shafique
Designing effective quantum models for real-world tasks remains a key challenge within Quantum Machine Learning (QML), particularly in applications such as credit card fraud detect…
QUAV: Quantum-Assisted Path Planning and Optimization for UAV Navigation with Obstacle Avoidance
Nouhaila Innan, Muhammad Kashif, Alberto Marchisio +3
The growing demand for drone navigation in urban and restricted airspaces requires real-time path planning that is both safe and scalable. Classical methods often struggle with the…
Next-Generation Quantum Neural Networks: Enhancing Efficiency, Security, and Privacy
Nouhaila Innan, Muhammad Kashif, Alberto Marchisio +2
This paper provides an integrated perspective on addressing key challenges in developing reliable and secure Quantum Neural Networks (QNNs) in the Noisy Intermediate-Scale Quantum…
Quantum Portfolio Optimization with Expert Analysis Evaluation
Nouhaila Innan, Ayesha Saleem, Alberto Marchisio +1
Quantum algorithms have gained increasing attention for addressing complex combinatorial problems in finance, notably portfolio optimization. This study systematically benchmarks t…
PennyCoder: Efficient Domain-Specific LLMs for PennyLane-Based Quantum Code Generation
Abdul Basit, Minghao Shao, Muhammad Haider Asif +4
The growing demand for robust quantum programming frameworks has unveiled a critical limitation: current large language model (LLM) based quantum code assistants heavily rely on re…
QAS-QTNs: Curriculum Reinforcement Learning-Driven Quantum Architecture Search for Quantum Tensor Networks
Siddhant Dutta, Nouhaila Innan, Sadok Ben Yahia +1
Quantum Architecture Search (QAS) is an emerging field aimed at automating the design of quantum circuits for optimal performance. This paper introduces a novel QAS framework emplo…
Optimizing Low-Energy Carbon IIoT Systems with Quantum Algorithms: Performance Evaluation and Noise Robustness
Kshitij Dave, Nouhaila Innan, Bikash K. Behera +3
Low-energy carbon Internet of Things (IoT) systems are essential for sustainable development, as they reduce carbon emissions while ensuring efficient device performance. Although…
QUIET-SR: Quantum Image Enhancement Transformer for Single Image Super-Resolution
Siddhant Dutta, Nouhaila Innan, Khadijeh Najafi +2
Recent advancements in Single-Image Super-Resolution (SISR) using deep learning have significantly improved image restoration quality. However, the high computational cost of proce…
Quantum Bayesian Networks for Machine Learning in Oil-Spill Detection
Owais Ishtiaq Siddiqui, Nouhaila Innan, Alberto Marchisio +2
Quantum Machine Learning (QML) has shown promise in diverse applications such as environmental monitoring, healthcare diagnostics, and financial modeling. However, its practical im…
Comparative Performance Analysis of Quantum Machine Learning Architectures for Credit Card Fraud Detection
Mansour El Alami, Nouhaila Innan, Muhammad Shafique +1
As financial fraud becomes increasingly complex, effective detection methods are essential. Quantum Machine Learning (QML) introduces certain capabilities that may enhance both acc…
LEP-QNN: Loan Eligibility Prediction using Quantum Neural Networks
Nouhaila Innan, Alberto Marchisio, Mohamed Bennai +1
Predicting loan eligibility with high accuracy remains a significant challenge in the finance sector. Accurate predictions enable financial institutions to make informed decisions,…
FL-QDSNNs: Federated Learning with Quantum Dynamic Spiking Neural Networks
Nouhaila Innan, Alberto Marchisio, Muhammad Shafique
We present Federated Learning-Quantum Dynamic Spiking Neural Networks (FL-QDSNNs), a privacy-preserving framework that maintains high predictive accuracy on non-IID client data. It…
MQFL-FHE: Multimodal Quantum Federated Learning Framework with Fully Homomorphic Encryption
Siddhant Dutta, Nouhaila Innan, Sadok Ben Yahia +2
The integration of fully homomorphic encryption (FHE) in federated learning (FL) has led to significant advances in data privacy. However, during the aggregation phase, it often re…
Federated Learning with Quantum Computing and Fully Homomorphic Encryption: A Novel Computing Paradigm Shift in Privacy-Preserving ML
Siddhant Dutta, Pavana P Karanth, Pedro Maciel Xavier +5
The widespread deployment of products powered by machine learning models is raising concerns around data privacy and information security worldwide. To address this issue, Federate…
AQ-PINNs: Attention-Enhanced Quantum Physics-Informed Neural Networks for Carbon-Efficient Climate Modeling
Siddhant Dutta, Nouhaila Innan, Sadok Ben Yahia +1
The growing computational demands of artificial intelligence (AI) in addressing climate change raise significant concerns about inefficiencies and environmental impact, as highligh…
QADQN: Quantum Attention Deep Q-Network for Financial Market Prediction
Siddhant Dutta, Nouhaila Innan, Alberto Marchisio +2
Financial market prediction and optimal trading strategy development remain challenging due to market complexity and volatility. Our research in quantum finance and reinforcement l…