BioI am an Associate Professor in the Allen School of Computer Science & Engineering at the University of Washington. I am also a PECASE Awardee and an Allen Distinguished Investigator. Previously, I did postdoctoral research at the University of Edinburgh and was a Ph.D. student at MIT.
ResearchMy current research is in the intersections of natural language processing, machine learning, and decision making under uncertainty. I am particularly interested in designing learning algorithms for recovering representations of the meaning of natural language text. For more research details, please see my publications.
- Winter 2018: Introduction to Artificial Intelligence (CSE 473)
- Spring 2016: Introduction to Artificial Intelligence (CSE 473)
- Winter 2016: Artificial Intelligence (CSEP 573)
- Terra Blevins
- Eunsol Choi (Co-advised with Yejin Choi)
- Chris Clark
- Nicholas FitzGerald
- Srinivasan Iyer (Co-advised with Alvin Cheung)
- Mandar Joshi (Co-advised with Dan Weld)
- Julian Michael
- Julian created a QA-SRL website that contains the QA-SRL Bank 2.0 data and an online parser demo. Please have a look!
- Congratulations to Nicholas, Julian, and Luheng for winning a best paper honorable mention award for Large-Scale QA-SRL Parsing at ACL 2018!
- Congratulations to Luheng, Kenton, and Omer for winning a best short paper honorable mention award for Jointly Predicting Predicates and Arguments in Neural Semantic Role Labeling at ACL 2018!
- Matt released code and pretrained models for ELMo. Please give it a try!
- Congratulations to Matt and team for winning a best paper award for Deep Contextualized Word Representations at NAACL 2018!
- Congratulations to Srini for winning an outstanding paper award for Learning to Map Context-Dependent Sentences to Executable Formal Queries at NAACL 2018! Although I wasn't involved in this work, I am always excited to highlight the achievements of group members (especially in a team with alumni)!
- We launched AllenNLP, a new open-source NLP research library built on PyTorch. AllenNLP includes reference models for an (ever growing) range of NLP tasks and infrastructure to make it easy to develop new deep learning approaches. Please give it a try!
- Congratulations to Mark for winning a best paper award for Men Also Like Shopping: Reducing Gender Bias Amplification using Corpus-level Constraints at EMNLP 2017! Although I wasn't involved in the work, I am excited to help publicize Mark's contributions to this important research!
- Congratulations to Kenton and Mike for winning a best paper award for Global Neural CCG Parsing with Optimality Guarantees at EMNLP 2016!
- Congratulations to Yoav and Kenton for winning a best paper award for Broad-coverage CCG Semantic Parsing with AMR at EMNLP 2015!