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Hi! I'm Ahmad Abdel-Qader, an AI leader and researcher working at the intersection of deep learning, domain generalization, and information theory.
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. I serve as a 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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