Yadu Prabhakar
Papers
2
Total Citations
39
H-Index
2
About
Yadu Prabhakar is a researcher at the forefront of autonomous systems, specializing in sensor fusion, deep learning, and self-driving car technologies. His work addresses one of the most critical challenges in robotics: the accurate and automated calibration of multi-sensor systems. Prabhakar’s major contributions include pioneering deep learning-based approaches for sensor auto-calibration, most notably through his development of "NetCalib," a novel framework for LiDAR-camera auto-calibration. This work, along with his broader research on "This Is the Way"—a deep learning approach for sensor auto-calibration in self-driving cars—has garnered significant attention, with his top papers accumulating 22 and 17 citations respectively. These contributions are vital for improving the reliability and accuracy of perception systems in autonomous vehicles, enabling safer and more efficient navigation. By automating the calibration process, Prabhakar’s research reduces manual intervention and enhances the robustness of sensor fusion, a cornerstone of modern robotics. His work continues to influence the development of scalable, intelligent systems for autonomous driving and beyond.
Research Focus
Key Achievements
Top Papers
- 1
- 2