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I have recently completed my PhD in Electrical and Computer Engineering at Toronto Metropolitan University, working under the guidance of Dr. Naimul Khan in the Multimedia Research Laboratory (RML). My expertise lies in Explainable Artificial Intelligence (XAI), Interpretable Machine Learning (IML), Healthcare AI and Fewshot-Learning. My research focuses on developing innovative computational methods to tackle complex challenges, with an emphasis on bridging the gap between theoretical advancements and practical applications. Email / CV / Google Scholar / LinkedIn / GitHub |
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Adjunct Faculty,
Odette School of Business, University of Windsor, Windsor, ON, Canada
April 2025 - Present |
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Professor - Partial Load,
Humber Polytechnic, Toronto, ON, Canada
January 2023 - Present |
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Professor - Part-time,
Seneca Polytechnic, Toronto, ON, Canada
January 2023 - Present |
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Graduate Teaching Assistant,
Toronto Metropolitan University, Toronto, ON, Canada
January 2018 - April 2022 |
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Muhammad Rehman Zafar, Naimul Khan International Joint Conference on Neural Networks (IJCNN), 2024 |
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Zeeshan Ahmad, Suha Rabbani, Muhammad Rehman Zafar, Syem Ishaque, Sri Krishnan, Naimul Khan IEEE Sensors Journal, 2023 |
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Muhammad Rehman Zafar, Naimul Khan Machine Learning and Knowledge Extraction (3)(3), 2021 |
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Muhammad Rehman Zafar, Naimul Khan ACM SIGKDD Workshop on Explainable AI/ML (XAI) for Accountability, Fairness, and Transparency, 2019 |
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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 |
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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. |
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PhD:
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