Nitin Surya
Papers
1
Total Citations
2
H-Index
1
About
Nitin Surya is a researcher at the intersection of robotics and reinforcement learning, with a focus on enabling machines to learn complex physical tasks through tactile feedback. His most-cited work, "Touch-based Curiosity for Sparse-Reward Tasks" (2021), introduces a novel intrinsic motivation mechanism that leverages force and torque sensors to guide exploration in contact-rich environments. By using surprise from mismatches in touch feedback, Surya’s approach allows robots to efficiently solve sparse-reward problems—such as assembly or manipulation—where traditional reinforcement learning struggles. This contribution is particularly impactful for real-world robotics, where tactile sensing is essential for tasks requiring delicate or precise contact. Though early in his career, Surya’s work has already garnered attention for bridging the gap between curiosity-driven exploration and physical interaction, offering a scalable path for robots to learn from touch. His research promises to advance autonomous systems in manufacturing, healthcare, and beyond, where safe and adaptive physical interaction is critical.
Research Focus
Key Achievements
Top Papers
- 1Touch-based Curiosity for Sparse-Reward Tasks2 citations · 2021