Dr. Jamil Fayyad | American University of Sharjah
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Profile

College / Department

College of Engineering
Department of Electrical Engineering

Teaching areas

Machine Learning and Deep Networks Intelligent Systems Computer Vision

Research areas

Vision–Language Models Continual & Incremental Learning Uncertainty-Aware Perception Systems

Education

PhD, Mechanical Engineering, University of British Columbia, Canada, 2023
Master, Mechatronics Engineering, American University of Sharjah, United Arab Emirates, 2012
Bachelor, Electrical Engineering, American University of Sharjah, United Arab Emirates, 2009

Contact

[email protected]
+971 6 515 4874

Dr. Jamil Fayyad

Assistant Professor
PhD, University of British Columbia, Canada

Jamil Fayyad is an Assistant Professor at the American University of Sharjah, which he joined in 2026. His research focuses on artificial intelligence, robot perception, and AI-driven medical imaging, with particular interests in developing robust and reliable intelligent systems. Prior to joining AUS, he gained experience across both academia and industry, working on applied AI and computer vision research in a range of real-world applications.

Publications

Mohamed Elkhayat, Mohamed Mahmoud, Jamil Fayyad And Nourhan Bayasi. Foundation Models as Class-Incremental Learners for Dermatological Image Classification, 2026
Mohamed Mahmoud, Shehab Khaled, Mohamed Elkhayat And Jamil Fayyad. On the Feasibility of Fr\'echet Radiomic Distance--Constrained Adversarial Examples in Medical Imaging: Methods and Trade-offs, 2026
Ashtyn Earl, Jamil Fayyad, Todd Charter, Maaike Van Kooten, Kate Jackson, Jean-pierre Véran, Homayoun Najjaran, Dirk Schmidt, Elise Vernet And Kathryn Jackson. Leveraging machine learning for PWFS reconstruction: bench validation with REVOLT, 19 August 2026
Nourhan Bayasi, Jamil Fayyad, Alceu Bissoto, Ghassan Hamarneh And Rafeef Garbi. BiasPruner: Mitigating bias transfer in continual learning for fair medical image analysis, Medical Image Analysis, December 2025
Nourhan Bayasi, Jamil Fayyad, Ghassan Hamarneh, Rafeef Garbi And Homayoun Najjaran. Debiasify: Self-distillation for unsupervised bias mitigation, 2025
Mohamed Elkhayat, Mohamed Mahmoud, Jamil Fayyad And Nourhan Bayasi. Foundation models as class-incremental learners for dermatological image classification, 2025
Jamil Fayyad, Nourhan Bayasi, Ziyang Yu And Homayoun Najjaran. Lesiongen: A concept-guided diffusion model for dermatology image synthesis, 2025
Nourhan Bayasi, Jamil Fayyad, Alceu Bissoto, Ghassan Hamarneh And Rafeef Garbi. Biaspruner: Debiased continual learning for medical image classification, 2024
Nourhan Bayasi, Jamil Fayyad, Alceu Bissoto, Ghassan Hamarneh And Rafeef Garbi. BiasPruner: Debiased Continual Learning for Medical Image Classification, 2024
Joel Sol, Jamil Fayyad, Shadi Alijani And Homayoun Najjaran. Sim-to-Real Domain Adaptation for Deformation Classification, 2024
Jaehoon Chung, Jamil Fayyad, Mehran Tamizi And Homayoun Najjaran. The Effectiveness of State Representation Model in Multi-Agent Proximal Policy Optimization for Multi-Agent Path Finding, 2024
Jamil Fayyad, Kashish Gupta, Navid Mahdian, Dominique Gruyer And Homayoun Najjaran. Exploiting classifier inter-level features for efficient out-of-distribution detection, Image And Vision Computing, 2024
Shadi Alijani, Jamil Fayyad And Homayoun Najjaran. Vision transformers in domain adaptation and domain generalization: a study of robustness, Neural Computing And Applications, October (4th Quarter/Autumn) 2024
Jamil Fayyad, Shadi Alijani And Homayoun Najjaran. Empirical validation of Conformal Prediction for trustworthy skin lesions classification, Computer Methods And Programs In Biomedicine, August 2024
Jaehoon Chung, Jamil Fayyad, Younes Younes And Homayoun Najjaran. Learning team-based navigation: a review of deep reinforcement learning techniques for multi-agent pathfinding, Artificial Intelligence Review, 8 February 2024
Jesse Roch, Jamil Fayyad And Homayoun Najjaran. Dopeslam: high-precision ros-based semantic 3d slam in a dynamic environment, Sensors, 2023
Jamil Fayyad. Out-of-distribution detection using inter-level features of deep neural networks, 2023
Jamil Fayyad, Mohammad Jaradat, Dominique Gruyer And Homayoun Najjaran. Deep Learning Sensor Fusion for Autonomous Vehicle Perception and Localization: A Review, Sensors, 29 July (3rd Quarter/Summer) 2020
Muhammad Zahid, Jamil Fayyad, Rached Dhaouadi, Shayok Mukhopadhyay And Nasser Qaddoumi. Optimal coil design for a quadrotor wireless charging system, 2019

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