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Hi! I'm Ahmad Abdel-Qader, a PhD researcher and industry AI leader working at the intersection of deep learning, domain generalization, and information theory.
I'm currently a PhD student in Computer Science at the University of British Columbia (UBC), where my research focuses on building robust, generalizable machine learning systems that continue to perform under real-world distribution shifts. My work spans domain generalization, representation learning, and learning-driven communication and coding insights, with an emphasis on principled methods and measurable reliability. Alongside my PhD, I serve as an Machine Learning Manager at Synthesis Health, where I lead end-to-end delivery of ML products from technical strategy and model development to mentoring engineers, aligning with stakeholders, and shipping systems into production. I combine research depth with execution and enjoy turning ideas into working, scalable solutions. Key Expertise: Deep Learning, Domain Generalization, Information Theory, Robust ML, Representation Learning, End-to-End ML Systems, AI Team Leadership |
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My research spans robust machine learning, domain generalization, and learning-driven communication and coding, with an emphasis on measurable reliability under distribution shift.
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A selection of software and systems projects spanning indoor localization, embedded IoT, and network simulation.
Links are provided when available.
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Lead Teaching Assistant (led 10 TAs)
Led the teaching team for team-based engineering design projects covering machine learning, probability, decision-making, and systems theory.
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Graduate Teaching Assistant
Core machine learning concepts and toolboxes, including supervised and unsupervised learning, with applications across engineering disciplines.
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Graduate Teaching Assistant
Team-based engineering design projects with practical use of machine learning, probability, decision-making, and systems theory.
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Last updated January 2026.
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