👋 Hi, I’m Amia.

I’m a Senior UX Researcher with 8+ years of experience shaping product strategy through mixed-methods research. With a background in Product Management, I take a strategic, business-aligned approach to UX—driving clarity in ambiguity and turning insight into impact.

My work sits at the intersection of human insight, cognitive science, and multimodal AI, exploring how to create emotionally intelligent, ethically grounded systems that build trust and connection.

I’ve led product innovation at conversational AI and neuroscience startups, as well as at Meta’s AI Research division (FAIR)—building UX research functions from the ground up and uncovering deep user needs.

Focus areas:

  • AI-human interaction

  • Behavioral science & habit formation

  • Multimodal experiences

I hold a BA in Cognitive Science and an MS in User Research / Human Factors, and am passionate about advancing the future of human–AI relationships.

Work.

Building an In-Car AI Voice Assistant System

Led foundational, generative, and evaluative UX research for a voice-AI car device and companion app, creating a seamless, hands-free driving experience.

My research secured a 50,000-device Walmart partnership, forged API integrations with iHeartRadio, TuneIn, and AccuWeather, and optimized the UX across hardware, mobile, and AI-human interactions to ensure a successful nationwide launch.

Enhancing Engagement for a Mental Health App

Led foundational, generative, and evaluative UX research for Matter, a neuroscience-backed mental health app designed to strengthen long-term well-being habits.

My research informed habit-forming features, gamification, clearer value propositions, and improved privacy—driving a 2× increase in onboarding conversion and a 210% boost in user engagement from beta to launch.

Exploring User Expectations for AI Assistants

This research was conducted prior to OpenAI’s launch of GPT’s native voice functionality, serving as one of the first explorations into user expectations and opportunities for LLM-driven voice interactions.

I led foundational and generative research to uncover how users engage with multimodal AI assistants and which characteristics make them most compelling. The findings directly shaped the company’s product roadmap—transforming an open question (“one assistant or many?”) into a data-driven strategy grounded in user trust, context awareness, and differentiated personas.