About
Dr. Ali Anaissi is a Lecturer in Data Science at the School of Computer Science, University of Sydney. His research focuses on structural health monitoring (SHM) using machine learning and sensor networks to detect damage in infrastructure such as bridges and roads. He has applied these techniques to the Sydney Harbour Bridge and developed a vehicle-mounted sensor system for road condition assessment. His work emphasizes condition-based maintenance over traditional time-based approaches. He teaches courses including Principles of Data Science (COMP5310), Machine Learning and Data Mining (COMP5318), and Software Development in Java (COMP9103).
His research spans structural damage detection, federated learning, tensor decomposition, and IoT applications in smart homes and healthcare. Key projects include developing a smart pothole detection system and exploring adversarial attacks in UAV services. He has authored numerous publications in journals like IEEE Transactions on Cybernetics and conferences such as IJCNN and ICDMW. His work integrates machine learning with domain knowledge to improve infrastructure safety and efficiency.
Dr. Anaissi's contributions include pioneering the use of adaptive one-class SVMs in SHM and developing frameworks for privacy-preserving fitness systems. His team's sensor-driven approaches aim to transform infrastructure maintenance through real-time health scoring and automated anomaly detection.
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