Summary
Siddharth Das is a software engineer specializing in robotics, perception, and ADAS with a decade of experience building safety-critical vehicle systems. With an MS in Robotics and Autonomous Systems from Arizona State University, he has applied multi-modal sensor fusion, JPDA with EKF, and LiDAR-validated localization to improve redundancy and reliability in production electric vehicles. At Canoo he led perception development, SIL test scenario design, and built a Python XVIZ-based DDS replay GUI that materially accelerated debugging and test automation. His work spans research and industry—from implementing Complex YOLO on 3D point clouds to deploying ML models on edge devices—demonstrating both experimental rigor and production engineering. Now at Ford, he brings cross-disciplinary strengths in computer vision, sensor fusion, and vehicle CAN tooling to scale ADAS solutions. Colleagues note his knack for translating academic research into practical tools that streamline testing and validation.
10 years of coding experience
6 years of employment as a software developer
B. Tech , B. Tech at Odisha University of Technology and Research
MS Robotics and Autonomous Systems(Artificial Intelligence) Mechatronics Robotics and Automation Engineering, MS Robotics and Autonomous Systems(Artificial Intelligence) Mechatronics Robotics and Automation Engineering at Arizona State University
Matriculation Intermediate Science , Matriculation Intermediate Science at Kendriya Vidyalaya, Puri