Swabha Swayamdipta

My research focuses on studying biases in datasets and models. Good biases, such as structural inductive biases help language understanding - check out my PhD thesis on these. But biases can be undesirable, e.g. spurious correlations commonly found in crowd-sourced, large-scale datasets due to annotation artifacts, or social prejudices of human annotators and task designers, which are difficult to rid!

Previously…

I obtained my PhD from Carnegie Mellon University in May 2019, where I was advised by Noah Smith and Chris Dyer. During most of my PhD I was a visiting student at the University of Washington in Seattle. I received a Masters degree from Columbia University where I was advised by Owen Rambow, and my B.Tech in CSE from NIT Calicut.

Update I will be starting as an Assistant Professor in the USC Viterbi Department of CS in Fall 2022!