My research interest is in bridging "system 1" and "system 2" reasoning. One approach I find promising lies in allowing neural networks to reason over the underlying graph structure of data, especially in domains where this structure is not provided. I believe that doing so requires insights from both machine learning and graph algorithms. I am also interested in demystifying neural networks through exploring their robustness.
I'm currently a senior undergraduate at Cornell University and am applying to PhD program 2020 fall.