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Agentic AI for the Era of XR

Samsung Research Institute, Bangalore - Internship (6 Months)

Overview


The project, ‘Agentic AI for the Era of XR’ was undertaken as part of my graduation project at MIT Institute of Design, Pune and internship with Samsung R&D Institute India, Bangalore.

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In recent years, AI and XR have rapidly progressed as separate technologies. However their convergence is now shaping a new direction for interactive digital experiences. With XR becoming more immersive and AI becoming more responsive there is a growing need to understand how they can work together to create intelligent interactions that feel natural human-like and efficient.

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While the core project is under NDA, this page outlines my design process, research approach and methodology, offering a glimpse into how I approached designing intelligent experiences.

Role

UX Research & XR Interaction Designer

Design Methodology

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Responsibilities

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  • Conducted extensive secondary research on AI embodiment trends, UX patterns and current product strategies.

  • Led primary user research, including qualitative interviews to uncover user pain points, emotional needs and embodiment preferences.

  • Defined design parameters for XR-based AI interactions (trust, proactiveness, non-human visual forms, emotional intelligence).

  • Created use case scenarios exploring agent behavior across wellness, productivity and social contexts.

  • Designed and evaluated multiple AI embodiment styles (realistic, stylized, abstract and minimal).

  • Delivered a comprehensive design proposal including user insights, UX strategy, concept designs and a POC.

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Research Highlights​

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  • Identified 5 embodiment types and mapped them to user values like trust, delight and task efficiency.

  • Developed a heatmap framework to evaluate how embodiment style affects user interaction and emotional connection.

  • Synthesized insights into personality models for AI that feel relatable but are not anthropomorphized unnecessarily.

Outcomes​

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  • A Proof of Concept simulating intelligent agent interactions.

  • Final documentation capturing research insights, user behavior mapping, design frameworks and prototype walkthroughs.

  • Positive feedback from internal mentors and academic jury on the future relevance and design maturity of the work.

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