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Aditya Shah
Junior Machine Learning Engineer specializing in computer vision and robotics
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About
Research assistant who single-handedly built and integrated an indoor autonomous wheelchair system using NVIDIA Jetson Nano, LiDAR, and a stereo camera. Implemented a multi-sensor perception pipeline (OpenCV/PCL) with ROS-based modular nodes, TF frame management, and robust debugging via RViz/rosbag, plus simulation testing in Gazebo and Dockerized environments for portability.
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Key Strengths
- End-to-end integration of perception + control stack for an autonomous wheelchair
- Built modular ROS architecture (sensor/perception/fusion/control) with clean topic interfaces
- Strong sensor fusion rigor: RViz validation, timestamp matching, noise filtering, confidence gating
- Systematic real-time debugging using rosbag replay to reproduce and isolate issues
- Resolved sim-to-real performance gaps via smoothing, hysteresis, and decoupled control rates
- Hands-on deployment readiness via Dockerized ROS environments
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Experience
Education
Awards
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Publications
1 publication
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