AI Safety & UX Researcher
Bridging Behavioral Science & AI Alignment
I'm a researcher with a Ph.D. in Experimental Psychology and 12+ years of experience across Google, Meta, and academia — studying how humans develop moral reasoning, form biases, and interact with AI. As a Staff-level UX Researcher at Insulet (previously at Meta Reality Labs and Google), I translate psychology research into concrete safety decisions, from driving compliance with trust and safety standards to reducing user harm in immersive VR environments. My work translates developmental & social psychology into actionable safety policies, harm taxonomies, and evaluation criteria that help AI systems behave in alignment with human values.
Background
My path to AI safety research began with a fundamental question: how do humans develop moral minds? Through years of cross-cultural fieldwork in Canada, India, Iran, and Korea, I built a granular understanding of how cognition, social norms, and reputation shape ethical behavior from childhood onward.
That foundation turned out to be surprisingly well-suited to some of AI's hardest problems. How should models reason about harm? What does it mean for an AI to be trustworthy? How do real users — including children — actually interact with and moralize AI agents? These are questions I've been researching, in various forms, for over a decade.
At Google and Meta I worked at the frontier of human-AI interaction — designing safety features, developing novel evaluation metrics, and partnering with ML and policy teams to ensure products protect users at scale. I bring both empirical rigor and product fluency to every research question I take on.
Notable Projects
Investigated how children and adolescents perceive home AI agents (Alexa, Siri). Found that reputation concerns and empathic interactions lead children to attribute moral standing to AI — directly informing youth-specific safety policy design.
AI Safety · Child DevelopmentField experiments in Canada, India, Iran, and Korea examining how laws, religion, and social norms shape children's moral development. Yielded a novel two-stage cross-cultural methodology directly applicable to global harm taxonomy design.
Cross-Cultural · Harm TaxonomyUsing experiments and economic games, showed that non-anonymous settings reliably increase ethical behavior in both children and adults — with direct implications for accountability and reward-based safety mechanisms in model training.
RLHF Relevance · AccountabilityCareer
Lead end-to-end research on AI-driven insulin delivery systems, supporting users of all ages living with diabetes.
Quest Spatial Awareness team — applied developmental and social psychology to adolescent safety in immersive tech.
Designed and led user studies for Google Beam, Google's AI-first 3D videoconferencing product.
Scholarship
Expertise
Get in Touch
I'm always interested in connecting with researchers and teams working at the intersection of behavioral science and AI. Feel free to reach out.