Linas Nasvytis

I am a second year PhD student at Stanford University, advised by Professor Judith Fan.

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

Before Stanford, I earned a master’s degree with a focus on 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 was working 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.

If you’d like to discuss any research ideas or have any questions, feel free to reach out by email!