I am interested in understanding how the brain builds internal models of the world and how emotional states influence the way we use these representations to learn, generalize, and make flexible decisions. My research combines behavioral experiments, neuroimaging, and computational modelling to understand how the brain represents abstract knowledge and how emotional states shape the cognitive maps that support learning, generalization, and adaptive behavior. Before joining the lab, I worked on topics spanning social cognition, interoception, and concept learning, including research on self-presentation in online dating, the influence of bodily rhythms on perceptual decision-making, and computational models of concept learning and hippocampal function. Prior to transitioning to psychology and neuroscience, I worked in computer science and engineering, where I applied machine learning and artificial intelligence methods, and in astrophysics, where I used high-resolution spectroscopy to study the chemical composition of stars and explore the history of our Galaxy. I remain involved in astrophysical research as a Research Associate at the Harvard-Smithsonian Center for Astrophysics and maintain open-source scientific software for the astronomy community. Across these disciplines, I have been motivated by a common interest in how complex systems can be understood through computation and empirical data. Today, that curiosity is focused on integrating principles from psychology, neuroscience, and computation to better understand human cognition and behavior.