I'm a scientist whose work lies at the intersection of neuroscience, cognitive science, and AI. I am primarily interested in understanding

(1) how minds, brains, and machines represent information about objects, concepts, and categories;

(2) how the form of these representations (i.e. representational geometry and topology) help achieve various cognitive functions;

(3) how systems with different learning mechanisms, like biological and artificial neural networks, learn, generalize, and develop representations with similar properties; and 

(4) how advances in mechanistic interpretability of machine learning models can enhance building safe, transparent, and reliable AI systems.

I received my PhD in Computational Cognitive Neuroscience from Rutgers University working in the Mind Brain Analysis group and the Brain Imaging Center and am currently a postdoc in the Bytes of Minds Lab in the Windreich Department for AI & Human Health at Mount Sinai. Previously, I was also a joint-postdoc in the Concepts and Actions Lab at Carnegie Mellon University and in the ProAction Lab at the University of Coimbra. Before that, I spent multiple years researching how children acquire and apply causal reasoning and causal inference in the Computational Cognitive Development Lab and at the Central European University's Cognitive Science Department. Once upon a time, I also used to be a linguist and received a MA in linguistics from the Utrecht University. 

Additionally, I'm also a big advocate for AI transparency and safety, which can only happen if we truly understand what the system's internal mechanisms are.