Yash Shah

Head of Scene Understanding at MOTOR Ai

Yash Shah has a strong background in autonomous vehicle technology and robotics. Yash is currently serving as the Head of Scene Understanding at MOTOR AI, leading a team of six members in the development of a Level 4 self-driving car. Yash's expertise includes localization, sensor fusion, object state estimation, future scene prediction, and traffic laws understanding. Yash is skilled in ROS2, AUTOSAR, Python, C++, computer vision, sensor data, and complex algorithms.

Prior to their current role, Yash worked as a Localization and Sensor Fusion expert, where they focused on state estimation and localization of Level 4 autonomous cars in unknown environments. Yash utilized probabilistic models such as Kalman filters, particle filters, and pose graphs to fuse uncertain GNSS, INS, and CANbus data. Yash also contributed to IMU bias estimation using Lidar and camera-based visual-inertial odometry measurements.

Yash's work experience also includes a research assistant position at Fraunhofer IFAM, where they worked on markerless 6-DOF pose estimation and tracking of moving objects using RGB-D cameras and lightweight robots. Yash developed codes for robot kinematics, control, and calibration, enabling the robot to track and follow objects.

Additionally, Yash completed their master's thesis at Hamburg University of Technology, focusing on autonomous patient motion compensation during needle insertion. Yash developed complex imaging algorithms based on feature extraction, optical flow, and ICP registration to estimate patient movements. The robot they worked with compensated for these movements in real-time.

Yash also gained experience as a software developer at Stadtreinigung Hamburg, where they developed a simulation of an autonomously navigating trash bin. Yash implemented features such as omnidirectional control, SLAM Gmapping, global path planning, object detection, and obstacle avoidance.

At Hamburg University of Technology, Yash led a research project involving medical robotics for autonomous needle insertion. Yash also participated in a cloud robotics application project for a telerehabilitation system.

Yash's career journey began with a role as a software developer for a fully autonomous car in the Formula Student competition. Yash gained knowledge of algorithms such as GMapping and Hector SLAM, as well as experience in ROS and Gazebo.

Before entering the field of robotics, Yash completed an internship in research and development at Vestas, a renewable energy company, and participated in the Design and Actuation team for Robocon at Gujarat Technological University.

Yash Shah completed their Bachelor of Engineering (BE) in Mechanical Engineering from Gujarat Technological University from 2014 to 2018. Yash then went on to pursue a Master of Engineering (MEng) in Mechatronics at Hamburg University of Technology from 2018 to 2021.

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Timeline

  • Head of Scene Understanding

    March, 2023 - present

  • Localization and Sensor Fusion expert

    February, 2022