Rehman Zafar
Rehman Zafar earned his PhD in Electrical and Computer Engineering from Toronto Metropolitan University, where he focused on advancing methods for explainability and interpretability in artificial intelligence. His research centers on Explainable AI, Interpretable Machine Learning, and Data Analytics, with an emphasis on developing ethical, transparent, and impactful AI systems for real-world applications.
He also brings extensive experience in software development, data science, and applied machine learning, leading projects that connect academic research with industry practice. His broader goal is to advance responsible AI that promotes fairness, accountability, and transparency in complex decision-making systems.
Programs / Courses taught
Advanced Data Analytics
Areas of academic interest
Artificial intelligence, machine learning, big data, predictive modelling, data mining
Areas of specialization
Explainable artificial intelligence, interpretable machine learning, responsible AI
Publications
- Muhammad Rehman Zafar, and Naimul Khan. "Attentional Feature Fusion for Few-Shot Learning." 2024 International Joint Conference on Neural Networks (IJCNN). IEEE, 2024.
- Zeeshan Ahmad, Syeda Rabbani, Muhammad Rehman Zafar, Syem Ishaque, Sridhar Krishnan, Naimul Khan. "Multi-level Stress Assessment from ECG in a Virtual Reality Environment using Multimodal Fusion," in IEEE Sensors Journal, 2023.
- Muhammad Rehman Zafar and Naimul Mefraz Khan. "Deterministic Local Interpretable Model-Agnostic Explanations for Stable Explainability". Machine Learning and Knowledge Extraction. 2021, 3, 525-541.
- Muhammad Rehman Zafar and Naimul Mefraz Khan. 2019. "DLIME: A Deterministic Local Interpretable Model-Agnostic Explanations Approach for Computer-Aided Diagnosis Systems". In Proceedings of Anchorage’19: ACM SIGKDD Workshop on Explainable AI/ML (XAI) for Accountability, Fairness, and Transparency (Anchorage’19).
- Muhammad Rehman Zafar and Munam Ali Shah. “Fingerprint authentication and security risks in smart devices.” 22nd International Conference on Automation and Computing (ICAC), 2016, pp. 548-553. IEEE, 2016.
Patents:
- Biggs, Edward W., L. O. W. E. Brianna, Justin Robert Caguiat, Naimul Mefraz Khan, Nabila Miriam Abraham, Muhammad Rehman Zafar, Syeda Suha Shee Rabbani, Zeeshan Ahmad, Mihai Constantin Albu, and Jacky Zhang. "Stress management in clinical settings." U.S. Patent Application 16/663,223 filed April 29, 2021.
