PECASE Awardee, Allen Distinguished Investigator

	Contact	Mailing Address
	Office: 658 Allen Center (directions)	Computer Science & Engineering
	Phone: 206-685-1227	University of Washington
	Fax: 206-685-2969	Box 352350
	Email: lsz@cs.washington.edu	Seattle, WA 98195-2350

I am an Associate Professor in the Allen School of Computer Science & Engineering at the University of Washington. I also lead a soon-to-be-named project at the Allen Institute for Artificial Intelligence. Previously, I did postdoctoral research at the University of Edinburgh and was a Ph.D. student at MIT.

Research

My 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 details, please see my publications.

Recent Teaching

• Spring 2016: Introduction to Artificial Intelligence (CSE 473)
• Winter 2016: Artificial Intelligence (CSEP 573)
• Winter 2015: Machine Learning (CSE 446)

Students (Alumni)

• Eunsol Choi (Co-advised with Yejin Choi)
• Nicholas FitzGerald
• Luheng He
• Srinivasan Iyer (Co-advised with Alvin Cheung)
• Mandar Joshi (Co-advised with Dan Weld)
• Kenton Lee
• Victoria Lin
• Julian Michael

Postdoc

• Omer Levy

Announcements

• 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!
• Kenton released a new neural coreference resolution model that is state of the art and uses no preprocessing. Check out the demo!
• Luheng released DeepSRL, an end-to-end neural SRL system that performs 4 F1 points better than any other publicly released PropBank model (a nearly 20% error reduction).
• Srini released code for interactive learning of neural semantic parsers that map from English directly to SQL. Now you can build and deploy a semantic parser that improves performance on its own over time, with just a little crowd sourcing!
• Yannis released his Neural AMR code, with models for mapping AMR to English and back. It includes state-of-the-art generation results and the best neural parser to date!
• Omer released his zero-shot relation extraction data and code. This work provides a new way of authoring relation extraction systems, where engineers simply specify natural language questions they want answered about target relationships!
• Congratulations to Kenton and Mike for winning a best paper award for Global Neural CCG Parsing with Optimality Guarantees at EMNLP 2016!
• Mark released ImSitu, a large, new situation recognition dataset. He has formulated this recognition problem as visual semantic role labeling, where images are mapped to structured action representations. Have a look at the data and recognition demo!
• Luheng released a QA-SRL dataset, demonstrating that non-expert annotators can provide supervision for recovering the predicative argument structure of English sentences.
• Congratulations to Yoav and Kenton for winning a best paper award for Broad-coverage CCG Semantic Parsing with AMR at EMNLP 2015!