Nitish Srivastava
Sr Director Of Autonomy at Serve Robotics
Cupertino, California, United States
Summary
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Senior🎓
Top SchoolNitish Srivastava is a seasoned autonomy and machine learning leader with 13 years of experience building perception, self-supervised, and reinforcement learning systems for embodied agents. Currently Sr. Director of Autonomy at Serve Robotics after co-founding Vayu Robotics and Clarevision Research (acquired by Apple), he blends deep research pedigree—PhD work with Geoffrey Hinton on dropout, Boltzmann machines and video models—with hands-on system delivery at Apple and startups. His work spans neural perception, sensor fusion, and production-ready convolutional network implementations (including early C++ GPU convnet contributions), evidencing both low-level engineering and algorithmic depth. Based in Cupertino, he’s equally comfortable shipping real-time autonomy stacks and publishing research-driven ML innovations, with a track record of turning academic ideas into deployed robotics capabilities.
13 years of coding experience
10 years of employment as a software developer
Indian Institute of Technology KanpurDoctor of Philosophy (PhD) Machine Learning, Doctor of Philosophy (PhD) Machine Learning at University of TorontoDelhi Public School - R. K. Puram
Github Skills (5)
neural-network10
convolutional-neural-networks10
c-language10
cprogramming-language10
hdf5
Programming languages (3)
Github contributions (5)
TorontoDeepLearning/convnet
Apr 2014 - Jun 2015
A GPU implementation of Convolutional Neural Nets in C++
Role in this project:
Backend Developer
Backend DeveloperContributions:182 commits, 2 PRs, 9 pushes in 1 year 2 months
Contributions summary:Nitish's initial commit introduces the core functionality of a convolutional neural network (CNN) in C++. Subsequent commits involve removing test features and making minor edits to the codebase. Their contributions are primarily focused on the core implementation and likely involve the structure, functionality and maintenance of the CNN implementation. The user also moved random number generation routines into a header file and has added a script to render the network as images.
cudagpunetsconvolutionalneural-nets
nitishsrivastava/deepnet
Dec 2012 - Jul 2014
Contributions:57 commits in 1 year 7 months
deep-learningmachine-learninglearning-algorithmsdeep-learning-algorithms
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