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Shubham Jangle
Intern Robotics Engineer specializing in autonomous navigation and perception (ROS2)
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About
Recent UC Riverside master’s graduate focused on uncertainty-aware imitation learning for indoor robot navigation, building a full ROS 2 Humble stack (perception, learned policy, uncertainty estimation) with adaptive speed control. Demonstrated strong real-time robotics debugging and systems skills, achieving 92% autonomous navigation success across 100 trials and improving reliability through uncertainty calibration and SLAM/loop-closure optimization.
Experience
Education
Key Strengths
- End-to-end ownership of robotics system architecture, implementation, training, and integration
- Delivered 92% task success (92/100 trials) for indoor navigation across three environments
- Strong ROS 2 systems integration (custom nodes + Nav2/TF2, sensor drivers, launch/params)
- Practical DDS/QoS tuning to resolve message drops and stabilize real-time pipelines
- Methodical debugging using RViz/RQT tooling, rosbag replay, and custom instrumentation
- Improved uncertainty reliability via calibration framework, dropout-rate tuning, and retraining on failure cases
- SLAM/loop-closure performance optimization (filtering, profiling, spatial indexing, non-blocking execution)
- Simulation-to-hardware workflow using Gazebo/Webots/MuJoCo and Dockerized environments
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