PhD candidate at Victoria University working at the intersection of cyber security, Internet of Vehicles, machine learning, and quantum computing. My work spans trust-aware federated learning for vehicular networks, quantum-enhanced learning pipelines, and vehicle network intrusion detection. I combine academic research with practical engineering and teaching.

• 🔭 Now: Finishing an integrated PhD that delivers secure, trustworthy federated learning for IoV and quantum-assisted model selection.
• 🧪 Interests: Federated learning, trust and reputation, adversarial robustness, quantum machine learning, IDS for autonomous vehicles.
• 🎓 Teaching: cybersecurity, Artificial Intelligence, Quantum computing instructor.

• Book: Cybersecurity in Robotic Autonomous Vehicles: Machine Learning Applications to Detect Cyber Attacks (CRC Press). DOI: 10.1201/9781003610908.
• Journal: Fed-DTB: A Dynamic Trust-Based Framework for Secure and Efficient Federated Learning in IoV Networks in Journal of Cybersecurity and Privacy, 2025. DOI: 10.3390/jcp5030048.
• Conferences: QFLAT: Quantum Federated Learning with Adaptive Trust for Secure and Efficient IoV Networks: An Innovative Approach

• Fed-DTB. Dynamic trust evaluation with multi-factor scoring and adaptive weighting for federated learning in vehicular networks. Focus on malicious client exclusion and reliable aggregation.
• QFLAT. Quantum Federated Learning with Adaptive Trust. Quantum support vector classification on IBM Quantum to improve participant selection and trust estimation in IoV.
• Autonomous Vehicle IDS. Python-based IDS targeting in-vehicle network anomalies for safety and resilience.
• YR Market Energy. Web application that identifies optimal days and times to schedule energy-intensive tasks based on weather-informed forecasts.
• LiminalVR “Mood States”. Mobile VR experience developed in Unity and C#.

• Quantum computing instructor covering Qiskit v2, NISQ programming, and applied quantum algorithms.
• Cybersecurity skills workshops on threat detection, security architecture, and vulnerability assessment.
• Python tutoring for individuals and small groups from fundamentals to advanced topics.

Skills summary

• Programming: Python, Java, C, C++, C#
• Front end: HTML5, CSS3, JavaScript, Bootstrap
• Data and machine learning: Pandas, scikit-learn, TensorFlow, PyTorch, Seaborn, OpenCV, MATLAB
• Systems and databases: Linux, Git, MySQL, Oracle, Hadoop, Node.js
• Design and XR: Figma, Sketch, Photoshop, Unity

• LinkedIn: linkedin.com/in/ahmed-alruwaili
• YouTube: @iovsecuretech