I am a PhD student in the Language Technologies Institute at Carnegie Mellon University. My advisors are Noah Smith and Chris Dyer. My research interests are primarily in structured prediction for natural language, with a focus on broad-coverage semantic parsing. In particular, I am interested in exploring new ways of incorporating syntactic cues and structural inductive biases to predict semantic structures for data across multiple domains, genres and languages. In addition to predicting semantic structures for language with high accuracy, I’m also interested in exploring how these structures can be utilized for downstream applications such as question answering.
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. I am currently an intern at the Allen Institute for Artificial Intelligence in Seattle. In the summer of 2017, 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.
Sep 17 2018: Attended the MSR AI Breakthroughs Workshop.
Aug 30 2018: Talk on Syntactic Scaffolds for Semantic Structures at NW-NLP 2018 now live!
Aug 20 2018: Co-presented the Multilingual FrameNet tutorial at COLING. [Slides and References]
Aug 10 2018: Long paper titled "Syntactic Scaffolds for Semantic Structures" accepted to EMNLP 2018!
Aug 05 2018: Pre-trained models now available for end-to-end frame-semantic parsing using open-sesame on both FN 1.5 and FN 1.7.