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About

Mudit Verma is a researcher working at the intersection of human-robot interaction, artificial intelligence, and cognitive modeling, with a particular focus on trust dynamics and the capabilities of large language models. His most impactful work investigates whether LLMs genuinely possess Theory of Mind abilities or merely simulate them, a critically examined question in the context of human-robot interaction that has garnered 18 citations since its 2024 publication. A significant thread running through Verma's research is the modeling of human trust in collaborative human-robot teams; his "Trust-Aware Planning" series explores how robots can reason about and actively cultivate trust over extended interactions, accumulating a combined 18 citations across multiple publications. He has further contributed to understanding how trust influences human monitoring behavior, offering empirically grounded models derived from controlled human subject studies. Beyond trust, Verma has expanded into reinforcement learning from human feedback, proposing methods that improve data efficiency by leveraging unlabeled trajectories. Collectively, his work addresses foundational challenges in building robots that are not only technically capable but socially intelligent and reliably collaborative — making him a noteworthy emerging voice in human-centered AI research.