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I received my PhD in Electrical and Software Engineering from Ontario Tech University in 2025 and my MSc in Computer Science from the University of Lethbridge in 2017. Prior to joining Wilfrid Laurier University, I was a Postdoctoral Fellow in the Faculty of Engineering and Applied Science at Ontario Tech University.
- Ontario Graduate Scholarship (OGS) – Awarded three times.
- Best Poster Award: “Anomaly Detection and Offense Prioritization for Smart Monitoring of Security Incidents.” SmartDelta: ITEA4 SmartDelta Project.
- University of Lethbridge Graduate Scholarships, International Research Award, Advantage Award.
My research focuses on improving software quality and reliability in large-scale continuous integration (CI/CD) systems through artificial intelligence and machine learning. I investigate methods for automated test case prioritization, fault prediction, and adaptive optimization using feature selection, hyperparameter tuning, and ensemble learning. My previous projects include industry-partnered collaborations on cybersecurity offense prioritization, anomaly detection in SOC environments, and software quality optimization in DevOps pipelines. This work aims to enhance testing efficiency, reduce costs, and advance the practical deployment of intelligent software engineering tools.
Peer-reviewed Journals
- Khan, M. A., Azim, A., Liscano, R., Smith, K., Chang, Y. K., Seferi, G., & Tauseef, Q. (2024). On the Effectiveness of Feature Selection Techniques in the Context of ML-based Regression Test Prioritization. IEEE Access.
- Khan, M. A., Tamim, I., Ahmed, E., & Awal, M. A. (2011). Multiple Parameter-Based Clustering (MPC): Prospective Analysis for Effective Clustering in Wireless Sensor Network (WSN) Using K-means Algorithm. Wireless Sensor Network, 4(1), 18-24.
Conference Proceedings
- Khan, M. A., Azim, A., Liscano, R., Smith, K., Chang, Y. K., Seferi, G., & Tauseef, Q. (2025, March 31–April 4). ML-Based Test Case Prioritization: A Research and Production Perspective in CI Environments. In Proceedings of the 18th IEEE International Conference on Software Testing, Verification and Validation (ICST).
- Khan, M. A., Azim, A., Abazari, F., Eargle, F., & Gardiner, J. (2024). Automated Offense Prioritization for SIEM Using Probabilistic Machine Learning Models. Canadian AI.
- Khan, M. A., Azim, A., Liscano, R., Smith, K., Chang, Y. K., Tauseef, Q., & Seferi, G. (2024, April). Machine Learning-Based Test Case Prioritization Using Hyperparameter Optimization. In Proceedings of the 5th ACM/IEEE International Conference on Automation of Software Test (AST 2024) (pp. 125-135).
- Khan, M. A., Singh, T., Azim, A., Burhanpurkar, V., & Perrin, R. (2021, October). Dynamic Kalman Filter-Based Velocity Tracker for Intelligent Vehicle. In IECON 2021 – 47th Annual Conference of the IEEE Industrial Electronics Society (pp. 1-6).
- Khan, M. A., Azim, A., Liscano, R., Smith, K., Chang, Y. K., Garcon, S., & Tauseef, Q. (2021, November). Failure Prediction Using Machine Learning in IBM WebSphere Liberty Continuous Integration Environment. In Proceedings of the 31st Annual International Conference on Computer Science and Software Engineering (pp. 63-72).
Workshops
Khan, M. A., Azim, A., Liscano, R., Smith, K., Chang, Y. K., Seferi, G., & Tauseef, Q. (2024, May). An End-to-End Test Case Prioritization Framework Using Optimized Machine Learning Models. In 2024 IEEE International Conference on Software Testing, Verification and Validation Workshops (ICSTW) (pp. 1-8).At Laurier University:
- CP214: Discrete Structure for Computer Science
- CP317: Software Engineering
- CP363: Database I
At Ontario Tech University:
- ENGR5010G: Advanced Optimization
- CSCI 3020U: Operating Systems