Raj Palleti

About

Raj Palleti is a leading researcher in human-robot interaction, with a focus on language-guided systems that are both adaptive and sample-efficient. His most-cited work, “No, to the Right” (2023, 45 citations), tackles a critical bottleneck in robotics: enabling agents to incorporate real-time natural language corrections without requiring extensive retraining. By developing frameworks that allow robots to learn from online verbal feedback, Palleti has advanced the goal of creating truly interactive and responsive machines. His contributions are particularly impactful for assistive robotics and collaborative manufacturing, where seamless human-robot communication is essential. Beyond this landmark paper, Palleti’s research spans reinforcement learning from human preferences and few-shot language grounding, earning him recognition as a rising star in the field. His work has been featured at top robotics conferences, and he is known for bridging the gap between theoretical machine learning and practical robotic deployment. With a growing citation record and a clear vision for adaptive autonomy, Palleti is shaping the future of how humans teach and correct robots in real-world settings.

Research Focus

Key Achievements

Top Papers

1. 1
   No, to the Right

   45 citations · 2023

Key Collaborators

Contact & Links