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Dr. Sajid Javed is an assistant professor of computer vision in the Department of Computer Science at Khalifa University of Science and Technology in the United Arab Emirates. He is affiliated with the Khalifa University Centre of Autonomous Robotics Systems (KUCARS) and the University of Warwick in the United Kingdom. Dr. Javed received his Ph.D. degree in Computer Science and Engineering from Kyungpook National University in the Republic of Korea and his B.Sc. (Hons) degree in Computer Science from the University of Hertfordshire in the United Kingdom. Prior to his current appointment, he worked as a research fellow at the University of Warwick, University Hospitals Coventry and Warwickshire in the United Kingdom, and KUCARS in the UAE. He leads the computer vision group within KUCARS and maintains active research collaborations across institutions.
Dr. Javed’s research focuses on computer vision, machine learning, and artificial intelligence, with particular emphasis on visual tracking from video sequences, multi-object tracking, object detection, background-foreground modeling, background subtraction, video object segmentation, histology image classification, tissue phenotyping, nucleus detection, and nucleus classification from routine Hematoxylin and Eosin Whole Slide Images. His work also extends to computational pathology and underwater computer vision applications. He has published extensively in leading venues including IEEE Transactions on Pattern Analysis and Machine Intelligence, IEEE Transactions on Image Processing, IEEE Transactions on Cybernetics, and Medical Image Analysis. Dr. Javed is a member of IEEE and ACM, serves as an associate editor for the International Journal of Computer Vision, and has held roles such as area chair for the Asian Conference on Computer Vision (ACCV 2022) and the International Conference on Robotics and Automation (ICRA 2023). He teaches courses including Artificial Intelligence, Advanced Computer Vision Paradigms, and Deep Learning System Design.
Khalifa University’s RoboGenAI enables underwater robots to interpret ocean data in real-time, detecting ecological changes for UAE aquaculture, desalination, and conservation.
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