Maz Khansari

Applied Computer Vision Machine Learning Scientist II at Amazon

San Diego, California, United States
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Summary

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Senior
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Maz Khansari is a machine learning and computer vision scientist with eight years of industry and academic experience, currently driving ML initiatives at Amazon's customer trust division. He has a strong track record translating research into production: leading six ML/CV projects at scale, collaborating with hundreds of scientists, and publishing internally and externally. Previously he pioneered 2D/3D medical imaging methods at USC and UIC, securing NIH funding and contributing to high-impact publications including work cited across the research community. Comfortable with both research and engineering, he builds end-to-end pipelines—from MATLAB/C++ image processing to TensorFlow/Keras models—and has shipped applied solutions such as an emotion-detection web app. Based in San Diego, he blends deep academic rigor (PhD and postdoc) with practical results that increased lab funding and adoption of novel biomarkers.
code8 years of coding experience
job8 years of employment as a software developer
bookPostdoc, Machine Learning and Computer Vision, Postdoc, Machine Learning and Computer Vision at University of Southern California
bookBachelor of Science (BS), Electrical and Electronics Engineering, Bachelor of Science (BS), Electrical and Electronics Engineering at Azad University (IAU)
bookDoctor of Philosophy (PhD), Biomedical Engineering, Data science, machine learning and medical image processing, Doctor of Philosophy (PhD), Biomedical Engineering, Data science, machine learning and medical image processing at University of Illinois Chicago
languagesEnglish
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Github Skills (36)

generative-model9
dcgan9
data-structure9
algorithm9
algorithms9
python9
cpp9
dtw8
autoencoder7
generative-adversarial-network7
medical-image-analysis6
tensorflow6
machine-learning-algorithms6
segmentation5
convolutional-neural-networks5

Programming languages (4)

C++JavaScriptJupyter NotebookPython

Github contributions (5)

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Contributions:20 commits, 8 pushes in 8 months
Contributions:1 release, 52 commits, 49 pushes in 1 year 2 months
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