About me

Hello, thanks for stopping by! My name is Naiti [IPA: neθi], and I am interested in how children learn about their worlds and interact with artificial systems.

My work has focused on the intersection of cognitive development, computational modeling, and artificial learning. I am especially interested in how insights from child development and cognitive science can help us understand, evaluate, and shape AI systems as they become more central to everyday life. I recently redirected my attention to focus on the impact and development of human-centered AI systems as questions about learning, feedback, and human-AI interaction are becoming increasingly important for protecting healthy cognitive development, especially for neurodivergent individuals.

I completed my postgraduate studies in the Department of Psychology at the University of Edinburgh, where I was advised by Hilary Richardson on a project studying the structural and functional neurodevelopmental changes underlying theory of mind reasoning in children. This work in developmental cognitive neuroscience combined functional and diffusion MRI, behavioral measurements, and reproducible analysis pipelines. Before Edinburgh, I graduated from Scripps College in May 2021 with majors in Computer Science and Neuroscience, advised by Tessa Solomon-Lane and Julie Medero. For my senior thesis, I worked with Bria Long and Michael C. Frank to characterize the inputs to early object learning and evaluate frontier computer vision model performance using egocentric frames collected from head-mounted cameras on infants. During college, I also completed NSF-funded Research Experiences for Undergraduates at the University of Minnesota’s Engel Vision and Imaging Lab and Stanford’s Language and Cognition Lab. After graduating, I worked as a lab manager in Catherine Hartley’s lab at New York University, where I was involved in projects formalizing models of reinforcement learning and decision-making over development.

Across these projects, I have become interested in the cognitive systems driving efficient learning: how people learn from experience, how they generalize, how they reason about others, and how those insights can inform the design and evaluation of AI that supports optimal learning across typical and atypical neural development.

I grew up in Basking Ridge in northern New Jersey (USA), named because “the wild animals of the adjacent lowlands were accustomed to bask in the warm sun of this beautiful ridge.” I like to roast and brew specialty coffee, chase sunrises and sunsets (ideally by hiking up hills or towards the sea), and swim in international waters (19 countries & 30 US states, coldest dip: 39°F/4°C).