Debadeepta Dey

Principal Architect at Microsoft

Greater Seattle Area United States
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Summary

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Rockstar
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Top School
Debadeepta Dey is a Principal Architect and AI Compiler specialist with nine years of professional experience building generative AI, machine learning, robotics, and computer vision systems. He has held senior research and leadership roles across Microsoft Research, Microsoft, and DataRobot, bridging deep academic rigor from a CMU PhD with product-focused engineering in the Greater Seattle area. His work spans foundations of perception and robotics to practical compiler and infrastructure problems for AI deployment, reflecting a rare combination of research-first thinking and systems-level delivery. As an affiliate faculty member at the University of Washington and a long-time CMU researcher, he frequently translates cutting-edge research into deployable technology. Notably, he moves fluidly between hands-on model and compiler design and high-level architectural decisions, accelerating how ML research becomes production-ready.
code10 years of coding experience
job13 years of employment as a software developer
bookStewart School
bookBachelor of Engineering Electrical, Bachelor of Engineering Electrical at Delhi College of Engineering
bookDoctor of Philosophy (Ph.D.) Robotics Machine Learning Computer Vision, Doctor of Philosophy (Ph.D.) Robotics Machine Learning Computer Vision at Carnegie Mellon University
bookHigh School, High School at Delhi Public School - R. K. Puram
languagesEnglish, Hindi, Bengali, Odia
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Github Skills (76)

python10
hyperparameter-optimization10
deep-learning10
automl10
model-compression10
neural-architecture-search10
java10
nas10
automated-machine-learning10
pytorch10
machine-learning10
imagenet9
convolutional-neural-networks9
ai9
platform-independent9

Programming languages (6)

TypeScriptJavaC++Jupyter NotebookMLIRPython

Github contributions (5)

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Contributions:602 commits in 1 year 3 months
microsoft/petridishnn

May 2019 - Sep 2020

Code for the neural architecture search methods contained in the paper Efficient Forward Neural Architecture Search
Contributions:22 commits, 6 pushes in 1 year 4 months
neural-architecture-searchdeep-learningdeep-learning-algorithmsimagenetcifar10
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