Elementary
Nambi Srivatsav has a diverse work experience in the field of robotics and software engineering. Nambi started their career as a Technical Head at the Indian Society for Technical Education and held this position from September 2010 to September 2012. Later, they worked as a Software Engineer at ShoreTel from July 2014 to July 2016, where they focused on the development of conferencing modules and contributed to new features and enhancements.
In 2016, Nambi joined Arizona State University as a Deep Learning Researcher in the Interactive Robotics Lab. Under the supervision of Professor Heni Ben Amor, they conducted research on deep learning for robotics. Nambi created and trained deep neural network architectures in simulation environments that they built from scratch for autonomous vehicle learning. In addition, they worked as a Drone Developer at Arizona State University from September 2016 to August 2017.
Nambi was an Robotics AI Intern at ABB from May 2018 to August 2018. During their internship, they trained ABB robots to learn bimanual manipulation using sample-efficient reinforcement learning. Nambi'swork resulted in an invention disclosure towards a patent application on machine learning for robotic manipulation.
Currently, Nambi is working as a Machine Learning Roboticist at Elementary Robotics, a position they have held since January 2019.
Nambi Srivatsav completed a Master's degree in Computer Science from Arizona State University, from 2016 to 2018. Prior to that, they obtained a Bachelor of Technology (B.Tech.) in Computer Science from Vellore Institute of Technology, from 2010 to 2014. Additionally, in December 2016, they earned a certification in Cryptography I from Stanford University online through Coursera Course Certificates.
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Elementary
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Elementary is a full-stack robotics startup that tackles Machine Learning for robotic hardware from the ground up with the goal to create assistive tools to improve the human output of repetitive tasks. Elementary provides easy-to-use software, deep learning AI, and camera systems are built to capture visual data, deliver fast and reliablereal-time judgments, and provide lasting value to the business. Elementary builds a hardware and software platform for applying machine learning and computer vision for intelligent automation of quality and traceability workflows in manufacturing and logistics.