DrMohamed Saadeldin

Dr. Mohamed Saadeldin received a B.Sc. (honours) in electrical & electronic engineering from the University of Khartoum, Sudan, in 2005. He was awarded the Ph.D. degree in computer science from University College Dublin (UCD), Ireland, in 2013.  Dr. Saadeldin worked previously as postdoctoral researcher at University College Dublin & also at King Abdullah University of Science and Technology (KAUST).

Dr Mohamed Saadeldin is currently an Assistant Professor at the School of Computer Science, University College Dublin, where he leads a research group focused on Generative AI, Multimodal Foundation Models, and Computer Vision. His work integrates fundamental advances in transformer architectures and representation learning with high-impact applications across healthcare, biomedicine, robotics, and intelligent energy systems. His research vision centers on designing scalable, trustworthy, and domain-adaptive foundation models that bridge data modalities and disciplines, enabling intelligent systems that are both scientifically rigorous and societally impactful. He currently supervises eight PhD students working on:

• Monocular Depth Estimation and 3D Vision for UAVs and robotics (3 students)
• AI and Transformer-based models for Medical Imaging (3 students)
• Generative AI for load disaggregation and smart grid optimization (industry-funded PhD)
• Generative AI for higher-education assessment and AI-augmented learning systems (1 student)

His recent research includes the development of vision foundation models for low-cost portable ultrasound in breast cancer screening, aiming to improve diagnostic access in low-resource settings. In collaboration with Systems Biology Ireland, he is building multimodal foundation models trained on multi-omic data to accelerate precision medicine and drug repurposing. He also leads an industry partnership on Transformer-based generative models for residential smart meter data, targeting scalable AI solutions for intelligent energy management, and has previously worked on ultrasonic detection, localization systems, IoT, and deep learning for agriculture.

Dr. Saadeldin has authored and co-authored 30+ peer-reviewed publications, including IEEE Transactions journals, major international conferences (e.g., CVPR, MICCAI), and a book chapter. He holds three registered U.S. patents, reflecting the translational and commercial potential of his research. 

In addition to research, he is deeply engaged in AI-driven education innovation, leading initiatives that integrate large language models into curriculum review, automated student support, and next-generation assessment systems. He is aiming to soon be appointed as incoming Director for Microcredential and Elective Courses at the UCD School of Computer Science.