Dhanasekar Karuppasamy
Papers
2
Total Citations
114
H-Index
2
About
Dhanasekar Karuppasamy is a leading researcher in autonomous systems and reinforcement learning, best known for pioneering the DeepRacer platform—an innovative, end-to-end experimental framework that bridges simulation and real-world robotics. His major contributions center on developing scalable, educational tools for Sim2Real transfer, enabling a 1/18th scale car to learn autonomous driving using only a monocular camera and reinforcement learning. This work directly addresses key challenges in intelligent control, such as domain adaptation and robust policy learning. His most-cited paper, "DeepRacer: Autonomous Racing Platform for Experimentation with Sim2Real Reinforcement Learning" (2020), has garnered 82 citations, while its 2019 precursor has 32 citations, collectively establishing DeepRacer as a foundational resource in the field. Beyond research, Karuppasamy’s platform has been widely adopted for education and competition, democratizing access to cutting-edge AI and robotics. His achievements include demonstrating practical Sim2Real transfer at scale, influencing both academic study and industry applications in autonomous navigation. Karuppasamy’s work continues to inspire students and researchers exploring the frontier of learning-based control.
Research Focus
Key Achievements
Top Papers
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- 2