Abhijeet Agnihotri

Senior Autonomous Systems Engineer - Incubation

Cupertino, California, United States
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Summary

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Senior
🎓
Top School
Abhijeet Agnihotri is a Senior Autonomous Systems Engineer with nine years of experience building human-centered robotics and AI systems across industry and academia. He has led human-robot interaction, prototyping, and ML-driven autonomy work at Toyota Research Institute, Aurora Flight Sciences (Boeing R&D), and now at Apple’s incubation team, focusing on making robots that empower people rather than merely automate tasks. His background blends mechatronics and expressive robot behavior research from Oregon State with hands-on product experimentation at X and Stanford, giving him a rare mix of rigorous HRI research and rapid prototyping instincts. Known for designing experiments that quantify human comfort and collaboration with autonomy, he repeatedly turns behavioral insights into deployable algorithms and hardware. Based in Cupertino, he pairs curiosity-driven exploration (“trying out stuff” on GitHub) with a practical track record of shipping novel robotics interactions.
code10 years of coding experience
job9 years of employment as a software developer
bookBachelor of Technology - BTech, Mechanical Engineering, Bachelor of Technology - BTech, Mechanical Engineering at Indian Institute of Technology, Patna
bookMaster of Science - MS, Mechatronics, Robotics, and Automation Engineering, Master of Science - MS, Mechatronics, Robotics, and Automation Engineering at Oregon State University
languagesHindi, English, Sanskrit, Japanese
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Github Skills (3)

skeleton-code4
deep-learning3
raspberry-pi1

Programming languages (2)

C++Python

Github contributions (5)

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abhiagni11/Deep-Learning-SDM

Feb 2019 - Aug 2019

As part of Sequential Decision Making course, this class project aims to leverage deep learning to solve the Sub-T challenge. This repository contains the base code to setup the simulator, test different planning approaches, and visualize the behavior of the system.
Contributions:58 commits, 2 PRs, 48 pushes in 6 months
deep-learning
Contributions:16 commits, 11 pushes, 1 branch in 10 days
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