Sahil Juneja
External Content Author (Independent Contractor) at Dataquest.io
Old Toronto, Ontario, Canada
Summary
👤
Senior🎓
Top SchoolSahil Juneja is a robotics and machine learning practitioner with 10 years of experience building curriculum and hands-on projects for online education platforms like Udacity and Dataquest. He blends deep technical expertise in robotics (inverse kinematics, UAV systems) and deep learning with a knack for translating complex concepts into clear, practical learning experiences. As a contributor to Udacity’s RoboND Pick-and-Place project, he’s improved core inverse-kinematics code and debugging tooling, reflecting a detail-oriented approach to both code and pedagogy. Based in Old Toronto, he pairs an M.S. focus in robotics with multiple Udacity nanodegrees, demonstrating continuous upskilling alongside professional work. Colleagues know him for improving student learning efficacy through thoughtful content design and rigorous technical review.
10 years of coding experience
3 years of employment as a software developer
Master of Science (M.S.), Electrical and Electronics Engineering (Focus on Robotics), Master of Science (M.S.), Electrical and Electronics Engineering (Focus on Robotics) at North Carolina State UniversityBachelor of Engineering, Mechatronics, Bachelor of Engineering, Mechatronics at Manipal Institute of TechnologySelf-Driving Car Nanodegree, Robotics, Deep Learning, Computer Vision, Self-Driving Car Nanodegree, Robotics, Deep Learning, Computer Vision at Udacity
English, Hindi
Github Skills (4)
robotics10
python10
debug9
debugging9
Programming languages (8)
Github contributions (5)
udacity/RoboND-Kinematics-Project
Jun 2017 - May 2018
Pick and Place project for RoboND Term 1
Role in this project:
Back-end Developer
Back-end DeveloperContributions:11 commits, 7 PRs, 9 pushes in 10 months
Contributions summary:Sahil's contributions primarily involve debugging and refining the Inverse Kinematics (IK) implementation within the project. Their work includes adding debugging tools, fixing typos, and updating comments to improve code clarity and understanding. They also added variables, possibly for the IK implementation, suggesting they were working on the core robotics-related functionality. The focus is on the IK code implementation within the context of the RoboND project.
placerobotics-simulationpick-and-placegazebosimpick
sahiljuneja/Udacity-SDCND-Term-1
Oct 2016 - Apr 2017
Udacity's Self-Driving Car Nanodegree Term 1 - Computer Vision and Deep Learning
Contributions:97 commits, 1 PR, 114 pushes in 5 months
pytorchtermnanodegreeudacityvision
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