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Gaurav Menghani

Staff Software Engineer at Google Research (Deep Learning, On-Device Machine Learning, Computer Vision)

Gaurav Menghani is a Staff Software Engineer at Google Research, where he leads several research projects focused on optimizing large ML models for efficient training and inference across various devices, from microcontrollers to Tensor Processing Unit (TPU)-based servers.12 His work has impacted over 1 billion active Google users across platforms like YouTube, Cloud, Ads, and Chrome.1

Menghani has over 11 years of experience in the tech industry.2 Before joining Google in 2017, he worked at Facebook for 4.5 years, contributing to Facebook's Search system and large-scale distributed databases.13 His research interests include Machine Learning, Algorithms, and Distributed Systems, with a current focus on Efficient Deep Learning.4

Academically, Menghani holds an M.S. in Computer Science from Stony Brook University (State University of New York).13 He is also an author of an upcoming book with Manning Publication on Efficient Deep Learning.1

Menghani is known for his contributions to the field of efficient deep learning. He has published a highly cited survey paper titled "Efficient deep learning: A survey on making deep learning models smaller, faster, and better" in ACM Computing Surveys.5 He has also been involved in various research projects and has several patents to his name, including one for "Application development platform and software development kits that provide comprehensive machine learning services".5

Highlights

‪Gaurav Menghani‬ - ‪Google Scholar‬
May 8 · mltechniques.com
New Book: Efficient Deep Learning - Machine Learning Techniques
New Book: Efficient Deep Learning - Machine Learning Techniques
May 13 · youtube.com
MLOps Event: Efficient Deep Learning by Gaurav Menghani
MLOps Event: Efficient Deep Learning by Gaurav Menghani
May 8 · gaurav.ai
Gaurav Menghani

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Gaurav Menghani
Gaurav Menghani, photo 1
Gaurav Menghani, photo 2
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Location

Mountain View, California, United States