8 papers
PHANTOM: Progressive High-fidelity Adversarial Network for Threat Object Modeling
Jamal Al-Karaki, Muhammad Al-Zafar Khan, Rand Derar Mohammad Al Athamneh
The scarcity of cyberattack data hinders the development of robust intrusion detection systems. This paper introduces PHANTOM, a novel adversarial variational framework for generat…
QI-MPC: A Hybrid Quantum-Inspired Model Predictive Control for Learning Optimal Policies
Muhammad Al-Zafar Khan, Jamal Al-Karaki
In this paper, we present Quantum-Inspired Model Predictive Control (QIMPC), an approach that uses Variational Quantum Circuits (VQCs) to learn control polices in MPC problems. The…
Achieving Optimal Tissue Repair Through MARL with Reward Shaping and Curriculum Learning
Muhammad Al-Zafar Khan, Jamal Al-Karaki
In this paper, we present a multi-agent reinforcement learning (MARL) framework for optimizing tissue repair processes using engineered biological agents. Our approach integrates:…
Optimal Path Planning and Cost Minimization for a Drone Delivery System Via Model Predictive Control
Muhammad Al-Zafar Khan, Jamal Al-Karaki
In this study, we formulate the drone delivery problem as a control problem and solve it using Model Predictive Control. Two experiments are performed: The first is on a less chall…
Predicting Water Quality using Quantum Machine Learning: The Case of the Umgeni Catchment (U20A) Study Region
Muhammad Al-Zafar Khan, Jamal Al-Karaki, Marwan Omar
In this study, we consider a real-world application of QML techniques to study water quality in the U20A region in Durban, South Africa. Specifically, we applied the quantum suppor…
Cybercrime Prediction via Geographically Weighted Learning
Muhammad Al-Zafar Khan, Jamal Al-Karaki, Emad Mahafzah
Inspired by the success of Geographically Weighted Regression and its accounting for spatial variations, we propose GeogGNN -- A graph neural network model that accounts for geogra…
Predicting Coronary Heart Disease Using a Suite of Machine Learning Models
Jamal Al-Karaki, Philip Ilono, Sanchit Baweja +3
Coronary Heart Disease affects millions of people worldwide and is a well-studied area of healthcare. There are many viable and accurate methods for the diagnosis and prediction of…
Deep Learning Under Siege: Identifying Security Vulnerabilities and Risk Mitigation Strategies
Jamal Al-Karaki, Muhammad Al-Zafar Khan, Mostafa Mohamad +1
With the rise in the wholesale adoption of Deep Learning (DL) models in nearly all aspects of society, a unique set of challenges is imposed. Primarily centered around the architec…