Sailik Sengupta
Papers
2
Total Citations
5
H-Index
2
About
Sailik Sengupta investigates the intersection of artificial intelligence, game theory, and human-robot interaction, with a central focus on trust and decision-making in autonomous systems. His major contributions lie in developing game-theoretic models that formalize how humans should monitor or trust robot behavior in collaborative settings. In his 2019 work, "To Monitor or to Trust," Sengupta addresses the critical tension between a robot’s cost-efficient plans and a human supervisor’s need for comprehensible, safe actions—a problem with direct implications for accountability in human-robot teams. His 2024 follow-up, "A Game-Theoretic Model of Trust in Human–Robot Teaming," further refines these ideas by guiding human observation strategies to mitigate risk when robot behavior deviates from expectations. Though his citation counts are currently modest (3 and 2 citations, respectively), his research tackles a foundational challenge in deploying autonomous agents: balancing efficiency with transparency. This work is particularly notable for its rigorous mathematical framing of trust as a strategic resource, offering a novel lens for designing safer, more reliable human-robot systems. Sengupta’s contributions are especially relevant for researchers in robotics, AI safety, and human factors engineering.
Research Focus
Key Achievements
Top Papers
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- 2