Background
My name is Mohamad Taghizadeh, and I am a researcher specializing in Artificial Intelligence (AI) applications in computer vision. I hold a Master’s degree in Electrical Engineering from the Iran University of Science and Technology (IUST), one of the top universities in Iran. My research has focused on deep learning techniques for image processing, particularly object detection and segmentation, leading to contributions to an IEEE conference paper on Sign Language Recognition and a recently published paper in IEEE Access on EEG signal processing. I have a strong background in machine learning, neural networks, and data-driven modeling, and I have served as a teaching assistant for multiple AI-related courses. My experience working with expert laboratories has allowed me to gain practical insights into applying AI methodologies to real-world challenges, fostering a deep understanding of advanced computational techniques.
Motivation
The growing reliance on artificial intelligence for infrastructure monitoring presents an exciting opportunity to develop innovative, data-driven solutions. This challenge motivates my involvement in the DC4 PhD project—BRIGITISE: WIM – Advanced Bridge Weigh-in-Motion (B-WIM) performance using vision-based data and machine learning. My project aims to improve bridge monitoring techniques by leveraging computer vision and AI to analyze structural behavior. This approach enables automated, real-time assessments without the need for costly sensor installations, offering a scalable and efficient solution for infrastructure management. By integrating AI with civil engineering applications, I aspire to contribute to the development of safer, smarter cities. This Ph.D. project will provide me with the opportunity to bridge the gap between research and industry, working at the intersection of advanced technology and real-world implementation. Ultimately, my goal is to develop AI-powered solutions that enhance the resilience and sustainability of critical infrastructure systems.