About

About Me

I am a research scientist at Springtail.ai researching methods to improve transformer learning sample efficiency.

While currently there is a lot of focus on scalability, I believe that true intelligence comes from learning to generalize under the constraint of limited samples and so am personally excited by sample efficient learning.

Previously I graduated from the University of Chicago, where I studied Computational Applied Math, Statistics, and Economics. During that time, I also studied machine learning theory and did machine learning research at the Toyota Technical Institute of Chicago.

I am a firm advocate of a growth and learning mindset. I am also a big believer in intuition- both in understanding and in explanation- and hope to share some of the things that I’ve learned here.

In my free time, I enjoy singing, learning about other people's stories (ex: through memoirs), and leisurely walks.
📖: Currently learning about efficient learning, meta RL