Muhammad Rehman Zafar

Welcome to my personal website. I am Dr. Muhammad Rehman Zafar, a researcher, educator, and technology consultant with a PhD in Electrical and Computer Engineering, specializing in Explainable Artificial Intelligence (XAI). My work spans academic research, industry collaboration, and higher education, with a strong focus on ethical, interpretable, and impactful AI systems.

Over the past decade, I have led initiatives in machine learning, big data analytics, and real-time AI deployment, and have taught a wide range of courses in data science and software engineering. I am passionate about bridging the gap between technology and business, mentoring the next generation of innovators, and contributing to meaningful, human-centered digital transformation.

Let's connect and explore how we can build a more intelligent, interpretable, and inclusive digital future.

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Academic Positions
Postdoctoral Researcher, Toronto Metropolitan University, Toronto, ON, Canada
June 2025 - Present
Adjunct Faculty, Odette School of Business, University of Windsor, Windsor, ON, Canada
April 2025 - Present
Professor - Partial Load, Humber Polytechnic, Toronto, ON, Canada
January 2023 - Present
Professor - Part-time, Seneca Polytechnic, Toronto, ON, Canada
January 2023 - Present
Graduate Teaching Assistant, Toronto Metropolitan University, Toronto, ON, Canada
January 2018 - April 2022
Publications
Attentional Feature Fusion for Few-Shot Learning
Muhammad Rehman Zafar, Naimul Khan
International Joint Conference on Neural Networks (IJCNN), 2024
Multilevel Stress Assessment From ECG in a Virtual Reality Environment Using Multimodal Fusion
Zeeshan Ahmad, Suha Rabbani, Muhammad Rehman Zafar, Syem Ishaque, Sri Krishnan, Naimul Khan
IEEE Sensors Journal, 2023
Deterministic Local Interpretable Model-Agnostic Explanations for Stable Explainability
Muhammad Rehman Zafar, Naimul Khan
Machine Learning and Knowledge Extraction (3)(3), 2021
DLIME: A Deterministic Local Interpretable Model-Agnostic Explanations Approach for Computer-Aided Diagnosis Systems
Muhammad Rehman Zafar, Naimul Khan
ACM SIGKDD Workshop on Explainable AI/ML (XAI) for Accountability, Fairness, and Transparency, 2019
Patents
Stress management in clinical settings
Edward W Biggs, Lowe Brianna, Justin Robert Caguiat, Naimul Mefraz Khan, Nabila Abraham, Muhammad Rehman Zafar, Syeda Suha Shee Rabbani, Zeeshan Ahmad, Mihai Constantin Albu, Jacky Zhang
United States, 2021
Industry Collaborations
Stress management in clinical settings
Collaborating with Shaftesbury VR, we developed a machine learning model for mutlimodal assessment of stress. The multimodal sensors can be physiological (e.g. EEG, heart-rate) and behavioural (e.g. facial expressions). The target is to use the assessed stress for Shaftesbury's Positive Distraction Entertainment System which adapts game content dynamically to reduce stress in children before a complex medical procedure, which can reduce complexity and recovery time.
Awards and Scholarships
PhD:
  • Toronto Met Graduate Fellowships
  • Toronto Met Graduate Development Award
  • Toronto Met International Student Scholarship
  • Toronto Met Graduate Travel Award
Master's:
  • Gold Medal for Academic Excellence
  • Open merit scholarship
  • Magna Cum Laude honor
  • Recognized in Rector’s Honor list (2015-2017)