Ankuj Arora

Papers

Total Citations

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About

Ankuj Arora is a researcher at the intersection of human-robot interaction (HRI) and autonomous behavioral systems, with a focus on enabling robots to seamlessly integrate into human social environments. His key research areas include robot speech modeling, speech act prediction, and the development of psycho-affective autonomy in machines. Arora’s most cited work, "Learning Robot Speech Models to Predict Speech Acts in HRI" (2016), addresses a critical gap in robotics: the need for robots to not only perform functional tasks but also exhibit socially intelligent, context-aware communication. By introducing methods for robots to autonomously predict and generate appropriate speech acts, his research lays groundwork for long-term behavioral autonomy, allowing robots to “camouflage” into physio-social contexts. This contribution has garnered 2 citations, reflecting its niche but foundational role in advancing socially adaptive robotics. Arora’s work is particularly notable for its emphasis on moving beyond mere functionality toward machines that can autonomously manage psycho-affective interactions—a step toward more natural, enduring human-robot relationships. His research is essential reading for those exploring autonomous social agents and the future of empathetic AI.