Close mobile menu

Author Image

Ruba Al Omari

Assistant Professor, Teaching Stream


Electrical Engineering & Computer Science


Dr. Ruba Al Omari is an Assistant Professor, Teaching Stream, in the Department of Electrical Engineering and Computer Science at York University. She holds a PhD in Computer Science and a Master's degree in Information Technology Security from Ontario Tech University, where she received the Doctoral Excellence Award.

Dr. Al Omari mainly teaches courses on security and is particularly interested in the use of Machine Learning in Cybersecurity.

Prior to her current role, Dr. Al Omari taught at Durham College and Ontario Tech University, where she also served as the program coordinator for the Artificial Intelligence – Honours Bachelor degree and the Cybersecurity Graduate Certificate at Durham College. With over 15 years of industry experience in IT, her background spans roles in user support, network management, and security.

Courses taught

Graduate Level:

  • Attack and Defense
  • Special Topics in IT: AI in Cybersecurity
  • Secure Software Systems
  • Security Policies and Risk Management
  • Biometric Access Control

Undergraduate Level:

  • Malware Analysis
  • Network Security and Forensics
  • Applied Cryptography
  • Introduction to Pen Testing
  • Hacking and Exploits
  • Incident Handling and Response
  • IT Security Policies and Procedures
  • Introduction to Machine Learning
  • Introduction to AI and Logic Programming
  • Operating System Fundamentals
  • Network Administration I & II

Capstone Courses:

  • Computer Security Project
  • Capstone I & II


  • Alomari, R., Martin, M. V., MacDonald, S., Maraj, A., Liscano, R., & Bellman, C. Inside out-A study of users’ perceptions of password memorability and recall. Journal of Information Security and Applications, Vol. 47:223-234. Elsevier, August, 2019.
  • Alomari, R., & Thorpe, J. On password behaviours and attitudes in different populations. Journal of Information Security and Applications, Vol. 45:79-89. Elsevier, April, 2019.
  • Alomari, R., Martin, M. V., MacDonald, S., & Bellman, C. Using EEG to predict and analyze password memorability. IEEE International Conference on Cognitive Computing (ICCC), (pp. 42-49). IEEE, July 2019.
  • Alomari, R., & Martin, M. V. Classification of EEG signals using neural networks to predict password memorability. In 17th IEEE International Conference on Machine Learning and Applications (ICMLA) (pp. 791-796). IEEE, 2018.
  • Alomari, R., Martin, M. V., MacDonald, S., Bellman, C., Liscano, R., & Maraj, A. What your brain says about your password: Using brain-computer interfaces to predict password memorability. In 15th annual conference on privacy, security and trust (PST) (pp. 127-12709). IEEE, 2017.
  • Bellman, C., Martin, M. V., MacDonald, S., Alomari, R., & Liscano, R. Have we met before? Using consumer-grade brain-computer interfaces to detect unaware facial recognition. Computers in Entertainment (CIE), 16(2), 1-17. ACM, 2018.
  • Bellman, C., Vargas Martin, M., Liscano, R., Alomari, R., & MacDonald, S. Excuse me, Do I know you from somewhere? Unaware facial recognition using brain-computer interfaces, 2017.
  • Bellman, C., AlOmari, R., Fung, A., Vargas Martin, M., & Liscano, R. Challenges in the effectiveness of image tagging using consumer-grade brain-computer interfaces. In Augmented Reality, Virtual Reality, and Computer Graphics: Third International Conference. Proceedings, Part II 3 (pp. 55-64). Springer, 2016.