Mrs. Narges Karimi is currently working at the University of Minho as a researcher on the project "Getty's Seismic Retrofitting," led by Prof. Dr. Paulo B. Lourenço. The project aims to develop a visual inspection system based on artificial intelligence to monitor the structural health of cultural heritage, with applications in Peru. The project is scheduled to be completed by 01-01-2025. Additionally, she is registered as a PhD candidate in civil engineering at the University of Minho (Portugal). Her research focuses on developing deterioration detection methods in historical buildings using artificial intelligence. Prior to this, she was involved in a similar project with the same supervisor for five months. Narges has already published three journal articles, two conference articles, and three datasets. One article was published in the International Journal of Architectural Heritage in 2023 (Impact Factor: 2.4), titled "Deterioration Detection in Historical Buildings with Different Materials Based on Novel Deep Learning Methods, with a Focus on Isfahan Historical Bridges." Another article was published in the Bagh-e Nazar Journal in 2016, which investigated the typology, developments, and damages in buttresses in Iranian architecture. Additionally, an article was published in the International Journal of Applied Arts Studies in 2017 (IJAPAS), focusing on the role of Sheikh Lotfollah Mosque's buttresses' defects in Iran. Currently, two articles have been submitted and are in the revision stage. One article focuses on automated tile defect detection in Portugal using deep learning, while the other focuses on crack detection in different materials of monuments using deep learning. Considering her ongoing work on damage detection in monuments and artificial intelligence, especially deep learning, the candidate has collected and labeled three different datasets of images of historical buildings that have been published on the Kaggle website. They are: the Deterioration Detection in Historical Buildings dataset, the CRACK-NO CRACK Classification Dataset, and the Tile Deterioration in Portuguese Historical Buildings dataset. She obtained her Master’s degree in Restoration and Renovation of Historical Buildings and Texture from the Art University of Isfahan, Iran. She also holds two Bachelor’s degrees: one in Restoration of Historical Buildings from the same university and another in Computer Science from Sheakh Bahaei University, Iran. She achieved the first-place position during her Master and Bachelor with an average grade of 19.19 and 18.66 respectively. She has over 4 years of experience in teaching and mentoring. Her expertise includes damage detection and pathology in monuments, image processing, machine learning, deep learning, data collection and labeling, flying drones, restoration and conservation of historical buildings, and documentation using laser scanning and photogrammetry. She is also an associate member of International Council on Monuments and Sites (ICOMOS). Her proposed PhD project aims to develop an autonomous AI-driven visual inspection system for cultural heritage buildings. The project will focus on implementing real-time damage detection using 3D models and testing them on a historic building in Portugal. The main objective of this project is to contribute to the conservation of monuments, aligning with the goals of the United Nations SDG 11.4.