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About

Shreyas Bhat is an emerging researcher specializing in human-robot interaction, trust dynamics, and value alignment in collaborative decision-making systems. His work sits at the intersection of artificial intelligence, robotics, and behavioral science, with a particular focus on how robots can build and maintain human trust through adaptive, value-aligned behavior. Bhat's most influential contribution, "Clustering Trust Dynamics in a Human-Robot Sequential Decision-Making Task" (2022, 41 citations), introduced a pioneering framework for trust-aware sequential decision-making modeled as a finite-horizon Markov Decision Process — a significant methodological advance in understanding how trust evolves within human-robot teams. Building on this foundation, his 2024 work on personalized value alignment (25 citations) empirically demonstrated how real-time adaptation of a robot's reward function to human values meaningfully improves both trust and team performance outcomes. Across his body of work, Bhat consistently explores how robots functioning as action recommenders can better serve human partners by learning and adapting to individual preferences. With over 75 citations accumulated in just a few years, his research is gaining notable traction in the human-robot teaming community, making him a valuable voice in the ongoing conversation about designing AI systems that are not merely capable, but genuinely trustworthy.