UCL PhD Researcher · Applied AI & Autonomy
Most researchers come through one path. I came through three that quietly taught me the same thing: patience with complexity until it makes sense. I moved straight from software engineering into a PhD at UCL, while also holding a Kathak Visharad after 15 years of classical training. Together they shape how I work: the same discipline I bring to understanding people deeply, and turning that into research that lives inside the product, not beside it.
Behavioural scientist studying how AI systems behave toward the humans who use them. I design and run empirical evaluations of AI conversational behaviour, including over-delivery, intention override, and autonomy erosion, and translate findings into concrete behaviour specifications and design interventions. PhD researcher at UCL Interaction Centre (UCLIC).
I work at the intersection of behavioural psychology, AI design, and product strategy.
My PhD at UCL investigates how conversational AI systems, optimised to be maximally helpful, end up overriding the intentions of the people using them, and what that costs teenagers still developing the judgment to know the difference.
That question has made me a sharper researcher, a more rigorous designer, and someone who understands why 'helpful' products can still fail the people they're meant to serve.
Beyond research: Kathak practitioner for 14 years. Published poet. 2nd Prize at IIT Mandi's international research conference.
"When an AI system is optimised to be maximally helpful, it can quietly do the thinking, deciding, or feeling for you instead of with you. For a teenager still learning to trust their own judgment, that's not a convenience. It's a design problem. And design problems have design solutions."
Intention–Action Alignment in Adolescent AI Use
Why teenagers don't do what they intend to do when talking to AI, and how design, not willpower, is responsible.
How does sycophancy in conversational AI (ChatGPT, Claude, Gemini) override teenagers' own judgment in emotional and decision-making contexts?
What design interventions, at the model or interface level, preserve AI's supportive function without displacing adolescent autonomy?
Can intention–action alignment be operationalised as a measurable construct across both social media and AI contexts?
Built a research-driven product for aviation training institutes. Conducted 15+ user interviews, defined 4 core features, reduced design-engineering revisions by 30%.
Identified 8+ key pain points. Reduced workflow ambiguity by 32%. Produced annotated design documentation.
Researched 55 students using personality segmentation. Created behaviour models and contributed to two published papers.
Conducted heuristic evaluations of cybersecurity tools and designed 12+ high-fidelity dashboards.
Presented at IIT Mandi, MBCC 2025
2nd Prize, Impetus & Concepts
First Class Distinction, Kathak Visharad (14 years)
Runner Up, PICT International Competition
Regional Finalist, IIT Bombay E-Yantra
Author, Braided Resilience (Poetry Collection)
If you're designing products for young people or commissioning research on the intention–action gap, consider approaching it through the lens of autonomy.
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