Dr. Saad Hashmi holds a PhD in Computing from Macquarie University, Australia (2020), an MSc in Computer and Software from Hanyang University, South Korea (2015), and a BSc in Computer Software Engineering from the Ghulam Ishaq Khan Institute, Pakistan (2011). In his doctoral research, Dr. Hashmi investigated the evolving landscape of ad-blocking tools and the compliance of mobile apps with their privacy policies. Through a longitudinal study of popular websites and apps, he addressed the critical question: Are ad-blocking tools and app privacy compliance improving or deteriorating over time? His research findings earned the Outstanding Paper Award at the 18th EAI International Conference on Mobile and Ubiquitous Systems (MobiQuitous) in 2021. Following his PhD, Dr. Hashmi served as a Research Fellow at the University of Wollongong, where he contributed to the development of an autonomic cyber resilience framework. Collaborating with CSIRO's Data61, DSTG, and Swinburne University of Technology, he integrated adversarial search and machine learning techniques to enhance the framework's capabilities. Dr. Hashmi's current research focuses on cyber resilience, privacy-preserving technologies, and innovative teaching pedagogies. With over 6 years of teaching experience at both undergraduate and postgraduate levels, he has delivered courses in programming, databases, data analytics, and cybersecurity, fostering a deep understanding of these domains among his students.

Hashmi, S.S., Dam, H.K., Chhetri, M.B., Uzunov, A.V., Colman, A. and Vo, Q.B., 2025. Proactive self-exploration: Leveraging information sharing and predictive modelling for anticipating and countering adversaries. Expert Systems with Applications, 267, article126118.

Hashmi, S.S., Waheed, N., Tangari, G., Ikram, M. and Smith, S., 2021, November. Longitudinal compliance analysis of android applications with privacy policies. In International Conference on Mobile and Ubiquitous Systems: Computing, Networking, and Services (pp. 280-305). Cham: Springer International Publishing.

Waheed, N., He, X., Ikram, M., Usman, M., Hashmi, S.S. and Usman, M., 2020. Security and privacy in IoT using machine learning and blockchain: Threats and countermeasures. ACM computing surveys (csur), 53(6), pp.1-37.