I am a graduate student in the EECS department at MIT. I am generally interested in studying how the biological brain and machine learning models learn efficient representations of knowledge and develop structures that support so.
My current focuses include but are not limited to the mechanistic interpretability of deep learning models and discovering biologically plausible rules that enable structural organization in the brain/models to emerge. I am broadly curious about using quantitative tools to investigate topics such as emergence properties in complex systems, intelligence, consciousness, and beyond.
Previously I worked on trapped-ion quantum computation as an undergrad at Duke University, where I studied physics and math.
In my free time, I enjoy weight-lifting, dancing, drawing, and hanging out with my dogs!