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PhD in Intelligent Transportation Systems (ITS), PhD in Automatics and Signals, Master in Electronics, Bachelor of Engineering (Electrical)
Dr Djamel Eddine is an experienced electrical engineer and researcher specialising in Automation, Deep Learning, and Intelligent Transportation Systems (ITS). His key areas of expertise include algorithm development, big data analytics, and designing and training complex deep neural mechanisms. He possesses advanced skills in various programming languages and embedded systems and is proficient with high-level programming languages, cloud computing platforms, and real-time multisensory applications. Djamel holds a PhD in Automatics and Signal Processing and a second PhD in ITS from the Queensland University of Technology (QUT). Attributed to his higher degree qualifications, he demonstrates multifaceted problem-solving abilities in diverse domains. Currently, he conducts research on High-Level Automated Vehicles (AVs) at the Centre for Accident and Road Safety – Queensland (CARRS-Q) at QUT. His PhD study focuses on vehicle motion prediction with social interaction awareness using deep multi-agent learning strategies and generative learning tools. During his PhD at QUT, he published his research findings in prestigious journals. He contributed to various projects on Connected and Intelligent Transportation Systems (C-ITS), including the iMOVE Cooperative and Highly Automated Driving (CHAD) and the safety risk evaluation of the remote operation of highly automated vehicles. Djamel’s current areas of knowledge encompass real-time robotic application development in Connected Automated Vehicles (CAVs), Generative AI-based applications, and Human-Machine Interaction (HMI) systems.
Awards and achievements
QUT ARC Linkage Scholarship – 2020
QUT Tuition Fee Scholarship – 2020