PhD (Monash), MSc (Japan), BSc Dr Quazi Mamun is an Associate Professor of Computing at the School of Computing, Mathematics, and Engineering at Charles Sturt University (CSU). He is also the school's HDR Coordinator, overseeing research training and doctoral programs. Dr Mamun holds a PhD in Distributed Computing from Monash University in Australia, an MSc in Global Information and Telecommunication Studies from Waseda University in Japan, and a BSc in Computer Science and Engineering from Bangladesh University of Engineering and Technology (BUET) in Bangladesh. Dr Mamun has over 23 years of experience in teaching, research, and industry collaboration. His expertise spans Software Engineering, Cybersecurity, AI-driven security, IoT, and Blockchain integration. He has led multidisciplinary research teams in designing and developing secure, scalable computing systems, strongly emphasising AI for cybersecurity, machine learning applications, and privacy-preserving distributed networks. As an active research leader and industry collaborator, Quazi has secured over $5 million in competitive research funding, partnering with organisations such as the Japan Science and Technology Agency, the Cyber Security Cooperative Research Centre (CSCRC), and global enterprises like GSK Global. He has published over 70 research papers, including more than 20 Q1 journal articles, and has delivered keynote speeches at prestigious conferences worldwide. Dr Mamun is a Senior Member of IEEE, a CISCO-certified Instructor, and an editor/reviewer for top-tier journals and conferences in computing and cybersecurity. His leadership extends to curriculum development, student mentoring, and accreditation efforts to align CSU’s computing programs with Australian Computer Society (ACS) standards. Dr Mamun is committed to student-centred learning, emphasising interactive, real-world applications of computing concepts. His teaching philosophy is based on three principles: Dr Mamun has revamped the curricula to include industry-relevant tools and methodologies, such as TensorFlow, PyTorch, and AI-driven security models. His approach of peer-based learning, real-world assessments, and work-integrated experiences has significantly boosted student engagement and success rates. Dr Mamun has taught a range of undergraduate and postgraduate courses, including: Dr Mamun's research interests include cybersecurity, AI-driven security, IoT, blockchain, and distributed systems. He has led high-impact projects in collaboration with global industry partners and has secured major research grants, including: Dr Mamun's research solves real-world security challenges, particularly in critical infrastructure protection, fintech, and AI-driven threat detection. Dr Mamun is actively involved in academic leadership, industry engagement, and professional service.Professorial Staff
Associate Professor Quazi Mamun
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