Amir Mohammadi is a research-focused machine learning engineer with six years of experience building computer vision and biometric systems, currently working on generative AI for images with realistic faces and embedded text at Idiap Research Institute. He holds a PhD-level background from EPFL and a strong track record in domain adaptation, anti-spoofing, and heterogeneous face recognition from multiple roles at Idiap and industry experience as Senior Data Scientist at Eyeware. At Eyeware he improved gaze and head tracking performance, scaled datasets tenfold, and cut infrastructure costs dramatically while shipping reproducible ML pipelines and a 20x faster visualization tool. Comfortable across research and production, he designs data collection protocols, synthetic data generation (including Unreal Engine renders), and optimized ML infrastructure. Colleagues know him as a practical problem-solver who blends deep academic rigor with hands-on engineering and a knack for making complex experiments reproducible and efficient.
6 years of coding experience
11 years of employment as a software developer
M.Sc. in Electrical and Electronics Engineering (With Thesis) Electrical and Electronics Engineering, M.Sc. in Electrical and Electronics Engineering (With Thesis) Electrical and Electronics Engineering at Özyeğin University
Doctor of Philosophy (PhD) Electrical and Electronics Engineering, Doctor of Philosophy (PhD) Electrical and Electronics Engineering at EPFL
Bachelor of Science (B.Sc.) Electrical/Biomedical Engineering bioelectric, Bachelor of Science (B.Sc.) Electrical/Biomedical Engineering bioelectric at University of Tehran
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