Shashank Rao Marpally
Papers
2
Total Citations
13
H-Index
2
About
Shashank Rao Marpally is a researcher at the forefront of human-robot interaction and explainable AI, with a sharp focus on how autonomous agents can communicate their decision-making processes to human teammates. His work addresses a critical gap in planning and robotics: while AI systems can generate technically accurate explanations, they often overwhelm humans by presenting too much information at once. Marpally’s key contribution, developed across two highly cited papers (2020 and 2021), is the concept of *progressive explanations*—a method that orders information incrementally to align with human cognitive capacity. By prioritizing the *order* in which explanations are delivered, his research ensures that humans can follow an AI agent’s reasoning step-by-step, reducing confusion and improving trust in human-robot teams. With over 13 combined citations, his work has been recognized for its practical relevance to real-world teaming scenarios, such as collaborative manufacturing or search-and-rescue operations. Marpally’s insight—that the *sequence* of explanation matters as much as the content—positions him as a rising voice in making AI not just intelligent, but genuinely understandable.
Research Focus
Key Achievements
Top Papers
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