Sunil Muralidhara
Papers
3
Total Citations
116
H-Index
2
About
Sunil Muralidhara is a researcher specializing in reinforcement learning, autonomous systems, and sim-to-real transfer — the challenging process of applying skills learned in simulated environments to real-world robotic platforms. He is best known as a key contributor to **AWS DeepRacer**, an influential educational autonomous racing platform that enables end-to-end experimentation with reinforcement learning using a 1/18th scale vehicle equipped with a monocular camera. This work, published across 2019 and 2020, has accumulated over 114 citations combined, demonstrating significant community impact and establishing DeepRacer as a widely adopted tool for both research and education in intelligent control systems. Muralidhara's contributions extend to simulation tooling as well, with his 2022 work on **DeepSim** — a reinforcement learning environment build toolkit for ROS and Gazebo — lowering barriers for machine learning researchers entering the robotics domain by enabling creation of complex custom simulation tasks. Collectively, his research bridges the gap between accessible educational platforms and rigorous scientific investigation, making reinforcement learning and autonomous systems research more approachable for students, educators, and researchers alike.
Research Focus
Key Achievements
Top Papers
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