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2 - 4 April, 2025 - Porto, Portugal

Within the 11th International Conference on Vehicle Technology and Intelligent Transport Systems - VEHITS 2025

CO-CHAIRS

	Waqar Shahid Qureshi University of Galway Ireland https://www.universityofgalway.ie/our-research/people/computer-science/waqarshahidqureshi/
Brief Bio Dr. Waqar Shahid Qureshi has 20 years of experience in R&D across academia and industry in computer science and engineering. He joined the University of Galway in January 2024 and is co-leading a project on surface condition assessment for cycle tracks in collaboration with Transport Infrastructure Ireland, TU Dublin, and Pavement Management Services. Previously, he developed a deep learning-based pavement assessment system at TU Dublin, leading to a patent. Dr. Qureshi has extensive industry engagement, having served as Vice Chief Software Engineer at XYZ Printing Ltd, developing commercial products and patents. He has collaborated internationally and led projects at NUST, Pakistan, including agricultural robotics and drone technologies, contributing to drone policy development.

	Ihsan Ullah University of Galway Ireland https://www.universityofgalway.ie/our-research/people/computer-science/ihsanullah/
Brief Bio Dr. Ullah did his Ph.D. from University of Milan, specializing in designing lightweight deep neural network architectures with the pyramidal approach. Have 13+ years of R&D experience in applying DeepLearning to a variety of images, video, text, and time-series recognition problems while working with renowned labs in US, Europe, and Middle East. Before joining School of Computer Science in Galway, he was a Senior Research Data Scientist in CeADAR Ireland's Centre for Applied AI in UCD where he was head of Special Projects group and was actively involved in applying for various national/international fundings e.g., HEU. Prior that, he worked as a Senior Postdoc, Adjunct Lecturer, and Project Manager of H2020 project 'ROCSAFE' at INSIGHT Research Centre in NUI Galway. Dr. Ihsan Ullah is currently the principal investigator of “Pav-Analytics: Intelligent Pavement Condition Rating System for Cycle Routes and Greenways”, a project focused on developing advanced AI-driven solutions to evaluate and rate the condition of cycling paths and greenways. This research leverages deep learning models and intelligent systems to ensure safer and more accessible routes for cyclists, with a particular emphasis on sustainability and mobility for diverse user groups. Previously, Dr. Ullah worked on road surface classification and rating, applying state-of-the-art machine learning and computer vision techniques to analyze and classify various road conditions. His years of computer vision and deep learning expertise in developing robust classification and regression systems has enabled practical applications in pavement maintenance strategies.

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