Archit Naik

Papers

Total Citations

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About

Archit Naik is a researcher at the forefront of human-robot interaction and social intelligence, whose work centers on modeling the complex, real-time dynamics of group behavior. His most cited paper, “Modeling social interaction dynamics using temporal graph networks” (2024, 2 citations), introduces a novel framework that captures the mutual influence between human actions and internal states—a critical step for enabling robots to collaborate naturally in fluid social settings. By addressing the limitations of static models, Naik’s approach leverages temporal graph networks to represent evolving social structures, offering a more robust foundation for autonomous systems to interpret and respond to group dynamics. This work not only advances the theoretical understanding of social interaction but also has practical implications for designing empathetic, context-aware robots. Naik’s research sits at the intersection of machine learning, social psychology, and robotics, promising to bridge the gap between artificial agents and human social environments. His contributions are particularly valuable for students and researchers exploring how intelligent systems can become truly integrated into our daily lives.