Hari Devanathan is a seasoned professional in software engineering and machine learning, with a robust background in teaching and technical writing. Experience includes roles at Microsoft as a Software Engineer optimizing IoT applications and multiple positions at Leidos as a Lead Machine Learning Engineer, where contributions involved developing advanced processing tools for medical records and designing serverless architectures for digital health. Additional roles encompass internships at notable organizations such as Epic and the University of Virginia's departments of Computer Science and Chemical Engineering. Currently pursuing a Master of Science in Analytics at Georgia Institute of Technology, Hari also contributes to Towards Data Science and CodeX as a Technical Writer specializing in machine learning.
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Charlottesville, United States
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