I am a behavioral scientist studying how people trust, interpret, and make decisions with artificial intelligence systems. My research examines the psychological mechanisms that shape when people appropriately rely on AI, when they over-trust it, and when they reject it — and what those patterns mean for the safe and responsible deployment of AI technologies. 

I am currently a Postdoctoral Researcher at the National Institutes of Health (National Human Genome Research Institute), where I study how individuals interpret AI-generated health information and how uncertainty framing shapes trust and decision-making in clinical contexts and how Virtual Reality can be integrated into clinical research practices. My doctoral research at Georgetown University examined mechanisms of trust in medical AI across six preregistered behavioral experiments with more than 3,000 participants, identifying the psychological processes that distinguish trust in AI systems from trust in human experts. 

My research combines experimental design, causal inference, statistical modeling, and mixed-methods approaches to answer a core question: how do people actually behave with AI systems, and what does that mean for how those systems should be built, evaluated, and deployed?

Research Interests:

• Trust calibration and appropriate reliance in human-AI interaction 
• Psychological mechanisms of algorithm aversion and algorithm appreciation 
• How AI systems should communicate reasoning and uncertainty to users 
• Societal and behavioral impacts of AI deployment at scale 
• Responsible AI design and evaluation

Selected Publications