Linas Nasvytis

I am a second-year PhD student at Stanford University, advised by Professor Judith Fan. I’m currently spending the summer as a Research Fellow at Goodfire, working on interpretable model improvement.

My research focuses on the intersection of human and machine intelligence. I am particularly interested in experience-efficient reasoning – how intelligent systems can quickly and continuously learn from minimal data or feedback from the outside world.

Before Stanford, I earned a master’s degree in statistical machine learning at the University of Oxford, working with Jakob Foerster, Christian Schroeder de Witt, and Chris Summerfield. I also spent a wonderful year at Harvard University collaborating with Sam Gershman and Fiery Cushman.

Before discovering the intersection of machine learning and cognitive science, I worked with Paul Romer at NYU, focusing on tech policy, cryptography, and economic research. I graduated from the Dual Bachelor’s progam between Columbia University and Institut d’études politiques de Paris.