Large language models (LLMs) are increasingly deployed in high-stakes settings such as finance, healthcare, and education, where failures in safety and fairness can cause real harm. In this dissertation, we advance LLM trustworthiness by (i) benchmarking how L…
This thesis addresses the growing need for Trustworthy AI, focusing on the transparency and privacy requirements. Transparency is commonly addressed through eXplainable AI (XAI), while privacy-preserving paradigms such as Federated Learning (FL) enable collabo…
Recent advances in visual and multimodal learning have demonstrated impressive performance on diverse tasks. However, their reliability in real-world scenarios remains challenged by issues of robustness, adaptation, and generalization. In this thesis, we tackl…
Generative artificial intelligence (AI) and its applications offer significant benefits but raise potentially critical societal and ethical concerns. This thesis explores the field of synthetic content generation and detection, with a particular focus on synth…
Large-scale pretraining has produced powerful deep learning representations, but real-world data rarely match the clean, uniform assumptions of standard transfer learning. This dissertation uses heterogeneous data to describe settings in which information diff…
Advancements in Machine Learning (ML) and distributed intelligence have accelerated the adoption of Federated Learning (FL) as a key enabler of privacy-preserving applications in domains such as IoT, healthcare, and Beyond 5G networks. FL enables collaborative…
With the rapid adoption of Artificial Intelligence across diverse applications, concerns around data privacy have become increasingly prominent. Traditional centralized machine learning approaches require aggregating large volumes of user data at a central ser…
This research project addresses the significant challenge of class imbalance in medical deep learning classification models, particularly when the abnormal class is underrepresented. Class imbalance can severely affect the classification performance of deep le…
The refractive index structure parameter, ??ₙ², quantifies optical turbulence and strongly influences the performance of electromagnetic and free-space optical systems operating within the marine wave boundary layer. Predicting ??ₙ² remains challenging due to…
Brain tumors are life-threatening conditions that require accurate and timely diagnosis. In clinical practice, diagnosis is commonly performed through Magnetic Resonance Imaging (MRI) analysis by medical experts, which is time-consuming and subject to variabil…
Artificial intelligence (AI) is being adopted in diverse fields, including medical diagnosis and scientific research, to assist with decision-making thanks to its ability to learn underlying patterns from large amounts of data. However, these advances present…
This thesis aims to provide a personal contribution to the research area of Trustworthy Artificial Intelligence (AI), focusing on some aspects still largely unexplored. The objective is to develop systems that achieve high predictive accuracy while creating tr…
أنا مساعد المستودع. اسألني عن الرسائل والأطاريح حسب الموضوع أو الجامعة أو الدولة أو السنة أو الدرجة، أو اطلب أعداداً وإحصاءات.
يجيب من قاعدة بيانات المستودع فقط، ولا يخترع سجلات أو أرقاماً. لا يُحفظ ما تكتبه على الخادم.
قد يخطئ المساعد أحياناً، فراجع المصادر المرفقة.
