Research interests

Machine learning, Large Language Models, AI for Cybersecurity, AI for Healthcare

Selected publications

Refereed Journal Articles

1. Michael Tawk, Samir Mustapha, Fouad Trad, Georges Saad (2025). Service Life Prediction in Pipelines Using Machine Learning Techniques. International Journal of Computational Intelligence Systems, Vol. 18.
2. Fouad Trad, Ali Chehab (2025). Evaluating the Efficacy of Prompt-Engineered Large Multimodal Models Versus Fine-Tuned Vision Transformers in Image-Based Security Applications. ACM Transactions on Intelligent Systems and Technology, Vol. 16.
3. Fouad Trad, Ryan Yammine, Jana Charafeddine, Marlene Chakhtoura, Maya Rahme, Ghada El-Hajj Fuleihan, Ali Chehab (2025). Streamlining Systematic Reviews with Large Language Models Using Prompt Engineering and Retrieval Augmented Generation. BMC Medical Research Methodology, Vol. 25.
4. Fouad Trad, Bassel Isber, Ryan Yammine, Khaled Hatoum, Dana Obeid, Mohamad Chahine, Rachid Haidar, Ghada El-Hajj Fuleihan, Ali Chehab (2025). Parsimonious and Explainable Machine Learning for Predicting Mortality in Patients Post Hip Fracture Surgery. Scientific Reports, Vol. 15.
5. Hawraa Nasser, Fouad Trad, Ali Chehab (2025). Stacking Large Language Models Is All You Need: A Case Study on Phishing URL Detection. Journal of Artificial Intelligence and Soft Computing Research, Vol. 15.
6. Zeina El Kojok, Hadi Al Khansa, Fouad Trad, Ali Chehab (2025). Augmenting a Spine CT Scans Dataset Using VAEs, GANs, and Transfer Learning for Improved Detection of Vertebral Compression Fractures. Computers in Biology and Medicine, Vol. 184.
7. Fouad Trad, Ali Chehab (2024). Prompt Engineering or Fine-Tuning? A Case Study on Phishing Detection with Large Language Models. Machine Learning and Knowledge Extraction, Vol. 6.
8. Fouad Trad, Elie Semaan-Nasr, Ali Chehab (2024). MLPhishChain: A Machine Learning-Based Blockchain Framework for Reducing Phishing Threats. Frontiers in Blockchain, Vol. 7.
9. Fouad Trad, Ali Hussein, Ali Chehab (2023). Leveraging Adversarial Samples for Enhanced Classification of Malicious and Evasive PDF Files. Applied Sciences, Vol. 13.
10. Fouad Trad, Salah El Falou (2022). Testing Different COVID-19 Vaccination Strategies Using an Agent-Based Modeling Approach. SN Computer Science, Vol. 3.

Refereed Conference Papers

1. Ali Mustafa, Fouad Trad, Ali Chehab (2025). Leveraging Large Language Models for Reducing False Positives and Prioritizing Alerts in Intrusion Detection Systems. In Proceedings of the 39th International Conference on Advanced Information Networking and Applications (AINA-2025), pp. 432–443, Springer, Barcelona, Spain.
2. Fouad Trad, Ali Chehab (2025). Manual Prompt Engineering Is Not Dead: A Case Study on Large Language Models for Code Vulnerability Detection with DSPy. In Proceedings of the 8th International Conference on Data Science and Machine Learning Applications (CDMA 2025), pp. 168–173, IEEE, Riyadh, Saudi Arabia.
3. Fatima Nasser, Fouad Trad, Marlene Chakhtoura, Ghada El-Hajj Fuleihan, Ali Chehab (2024). Accelerating Systematic Reviews via Natural Language Processing. In Proceedings of the 6th International Conference on Computer and Applications (ICCA 2024), pp. 1–11, IEEE, Cairo, Egypt.
4. Fouad Trad, Ali Chehab (2024). Large Multimodal Agents for Accurate Phishing Detection with Enhanced Token Optimization and Cost Reduction. In Proceedings of the 2nd International Conference on Foundation and Large Language Models (FLLM 2024), pp. 229–237, IEEE, Dubai, UAE.
5. Ibrahim El Didi, Fouad Trad, Ali Chehab (2024). Enhancing Network Security Through Deep Learning: Mitigating Feature Engineering and Zero-Day Attacks. In Proceedings of the 4th Intelligent Cybersecurity Conference (ICC 2024), pp. 127–131, IEEE, Valencia, Spain.
6. Fouad Trad, Ali Chehab (2024). To Ensemble or Not: Assessing Majority Voting Strategies for Phishing Detection with Large Language Models. In Proceedings of the 4th International Conference on Intelligent Systems and Pattern Recognition (ISPR 2024), pp. 158–173, Springer, Istanbul, Turkey.
7. Fouad Trad, Ali Hussein, Ali Chehab (2023). Assessing the Effectiveness of Siamese Neural Networks to Mitigate Frequent Retraining in IoT Device Identification Models. In Proceedings of the 9th International Conference on Platform Technology and Service (PlatCon 2023), pp. 47–52, IEEE, Busan, South Korea.
8. Fouad Trad, Ali Hussein, Ali Chehab (2022). Free Text Keystroke Dynamics-Based Authentication with Continuous Learning: A Case Study. In Proceedings of the 21st International Conference on Ubiquitous Computing and Communications, pp. 125–131, IEEE, Beijing, China.
9. Fouad Trad, Ali Hussein, Ali Chehab (2022). Using Siamese Neural Networks for Efficient and Accurate IoT Device Identification. In Proceedings of the Seventh International Conference on Fog and Mobile Edge Computing, pp. 1–7, IEEE, Paris, France.
10. Fouad Trad, Salah El Falou (2022). Towards Using Deep Reinforcement Learning for Better COVID-19 Vaccine Distribution Strategies. In Proceedings of the 7th International Conference on Data Science and Machine Learning Applications, pp. 7–12, IEEE, Riyadh, Saudi Arabia.
11. Salah El Falou, Fouad Trad (2021). Forecast Analysis of the COVID-19 Incidence in Lebanon: Prediction of Future Epidemiological Trends to Plan More Effective Control Programs. In Proceedings of the Sixth International Conference on Advances in Biomedical Engineering, pp. 135–140, IEEE, Werdanyeh, Lebanon.

Academic Degrees

PhD,  Electrical and Computer Engineering, American University of Beirut, Lebanon, 2025
M.S.,Technology of Communicating, Medical, and Industrial Systems, Lebanese University, Lebanon, 2021
B.E., Computer and Communication Engineering, Lebanese University, Lebanon, 2021

Memberships

• IEEE (Institute of Electrical and Electronics Engineers)
• ACM (Association for Computing Machinery)
• Order of Engineers and Architects, Tripoli, Lebanon.