swabha swayamdipta

185 Stevens Way, Box 352350, Seattle WA

I am a final year PhD student in the Language Technologies Institute at Carnegie Mellon University, advised by Noah Smith and Chris Dyer. My research interests are primarily in structured prediction and representation learning for natural language. In particular, my thesis explores methods for incorporating syntactic inductive biases, either from observed or latent syntax, to learn robust representations of language, helpful in structured prediction across tasks and languages.

Since Aug 2015, I have relocated to Seattle, and have been a visiting student at the Paul G. Allen School of Computer Science and Engineering at University of Washington, Seattle. In the summer and fall of 2018, I interned at the Allen Institute for Artificial Intelligence in Seattle. In the previous summer, I interned at Google AI Language in New York.

In 2013, I graduated from a Masters program at Columbia University, where I was advised by Owen Rambow. During this period, I worked on detection of influence and power in online social media.