Biography

Dr. Mohsin Murtaza is an Assistant Professor in Business Analytics at the College of Business, Al Ain University. He has over ten years of teaching experience across multiple reputable Australian institutions, including RMIT Univeristy, La Trobe University, Charles Sturt University, and Central Queensland University, where he has contributed to curriculum design, course development, and accreditation processes. His teaching philosophy emphasizes student engagement, practical application, and fostering analytical and research-driven thinking.

 Dr. Murtaza has been recognized multiple times for his innovative teaching and commitment to student success, earning several Teaching Excellence Awards and Pro Vice-Chancellor’s Awards for exceptional course development, student satisfaction, and learning outcomes.

 His research spans Artificial Intelligence (AI), Business Analytics, Busienss Intelligence, Autonomous Systems, Information Systems, and the effectiveness of AI in teaching, learning, and professional training contexts. He has actively published in reputable international journals and conferences and has also secured competitive research funding through the Enabling Impact Platform (EIP), reflecting the applied and impactful nature of his scholarly work.

 Beyond academia, Dr. Murtaza has delivered training and consultation to government, public-sector, and industry personnel in areas such as analytics, systems, and emerging technologies. He also serves on technical committees for international conferences, reviews for reputable journals, and regularly participates in professional development activities to advance his academic and research practice.

Education

• Doctor of Philosophy, RMIT University, Australia. (Research Focus: Artificial Intelligence, Applied Data Analytics, and Business Analytics)
• Graduate Diploma of Business Information Systems, Federation University, Australia
• Master of Telecommunication Engineering, La Trobe University, Australia
• Bachelor of Science (Telecommunication Engineering), National University of Computer and Emerging Sciences (NUCES-FAST), Pakistan)
• TAE40116-Certificate IV in Training and Assessment, Plenty Training, Australia
• TAE40110-Certificate IV in Training and Assessment, Training and Development Institute, Australia

Research Interests

Artificial Intelligence (AI), Business Analytics, Data Analytics, Human–AI Interaction, Generative AI Applications in Education and Healthcare, AI-Enhanced Teaching and Learning, Responsible AI-Ethics and Governanc  Information Systems, and Cybersecurity,.

Selected Publications

• Islam, U., Ullah, H., Almaiah, M.A., Khamis, A.A.A., Murtaza, M., Iftikhar, M. and Shah, P.A., 2026. FedDrive-Sec: A blockchain-assisted federated deep reinforcement learning framework for secure and adaptive Internet of Vehicles. Telematics and Informatics Reports, p.100312.

  Kagai, F., Murtaza, M., Arachchige, K.G. and Albahlal, B.M., 2026. Mobility-aware adaptive bandwidth selection in IEEE 802.11ah Wi-Fi HaLow for infrastructure-limited rural connectivity. IEEE Access.

• Arsalan, A., Umer, T., Rehman, R.A., Kim, B.S., Murtaza, M. and Cheng, C.T., 2026. Semantic-aware communication and computation co-optimization in digital twin-assisted Internet of Drones networks using federated deep reinforcement learning. ICT Express.
• M. Murtaza, C-T, Cheng, B.M, Albahal, M.M. Muslama, and M.Raza “The Impact of LLM Chatbots on Learning Outcomes in Advanced Driver Assistance Systems Education, Nature-Scientific Report, 2025, doi:10.1038/s41598-025-91330-3 .
• M. Murtaza, M. Iftikhar, M. S. Raza, Z. H. Mir, M. J. Abdulaal, and N. Nasser, “Integrating IoT and Cloud for Enhanced Autonomous Vehicle Safety,” in Proc. IEEE Middle East Conf. Commun. Networking (MECOM), Nov. 2024, pp. 362–367.
• K. G. Arachchige, G. Alkaabi, M. Murtaza, Q. E. U. Haq, A. Z. Abualkishik, and C. C. Lee, “Threat Landscape and Integrated Cybersecurity Framework for V2V and Autonomous Electric Vehicles,” World Electric Vehicle Journal, vol. 16, no. 8, p. 469, 2025.
• M. Murtaza, C.-T. Cheng, M. Fard, and J. Zeleznikow, "Transforming Driver Education: A Comparative Analysis of LLM-Augmented Training and Conventional Instruction for Autonomous Vehicle Technologies," International Journal of Artificial Intelligence in Education, pp. 1-38, 2024, doi: 10.1007/s40593-024-00407-z .
• M. Murtaza, C.-T. Cheng, M. Fard, and J. Zeleznikow, "Assessing Training Methods for Advanced Driver Assistance Systems and Autonomous Vehicle Functions: Impact on User Mental Models and Performance," Applied Sciences, vol. 14, no. 6, p. 2348, 2024, doi: 10.3390/app14062348.
• K.Godewatte, M. Murtaza, and C.-T. Cheng, " Blockchain-Enabled Mitigation Strategies for Distributed Denial of Service Attacks in IoT Sensor Networks: An Experimental Approach", Computers, Materials &Continua, 2024.
• M. Murtaza, C.-T. Cheng, M. Fard, and J. Zeleznikow, "Preparing Drivers for the Future: Evaluating the Effects of Training on Drivers’ Performance in an Autonomous Vehicle Landscape," Transportation Research Part F: Traffic Psychology and Behaviour, 2023, doi: 10.1016/j.trf.2023.09.013.
• M. Murtaza, C.-T. Cheng, M. Fard, and J. Zeleznikow, "The importance of transparency in naming conventions, designs, and operations of safety features: from modern ADAS to fully autonomous driving functions," AI & SOCIETY, pp. 1-11, 2022, doi: 10.1007/s00146-022-01442-x 

 

 

 

Teaching Courses

• Artificial Intelligence in Business
• Business Analytics
• Introduction to Business Analytics
• Scientific Research Methodology
• Business Intelligence
• Statistics for Business Decissiness Intelligion Making
• Business Data Communications

 

 

Expertise related to UN Sustainable Development Goals

In 2015, UN member states agreed to 17 global Sustainable Development Goals (SDGs) to end poverty, protect the planet and ensure prosperity for all.

This person’s work contributes towards the following SDG(s):