Ishaan Grover

Papers

Total Citations

161

H-Index

About

Ishaan Grover is a leading researcher in the intersection of artificial intelligence, social robotics, and early childhood education. His work focuses on developing personalized, affect-aware learning companions that can adapt to children’s emotional and cognitive states in real time. Grover’s most influential contribution is his model-free affective reinforcement learning approach, which enables autonomous social robots to deliver tailored educational interventions for early literacy. This work, published in 2019 and cited over 140 times, demonstrates how robots can leverage children’s behavioral and affective cues to improve learning outcomes. His research also explores the dynamics of long-term human-robot interaction, co-authoring a seminal chapter on relational socially interactive agents (SIAs) that synthesizes two decades of progress in the field. Grover’s studies on storytelling interactions, such as the P2PSTORY system, further highlight his commitment to understanding social-emotional behaviors in child-robot engagement. By combining reinforcement learning, affective computing, and developmental psychology, Grover is shaping the next generation of adaptive educational technologies that are responsive, empathetic, and capable of fostering meaningful, sustained relationships with young learners.