About

About Me

I am a research scientist at Springtail.ai researching sample efficient learning methods for AI reasoning.

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.

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 researched machine learning (specifically reinforcement learning) 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), leisurely walks, and writing.