Bios of Tutorial 1 Presenters

Alane Suhr

PhD Student, Cornell University
Alane's research focuses on grounded natural language understanding. Alane has designed crowdsourcing tasks for collecting language data to study situated natural language understanding. Alane co-presented a tutorial in ACL 2018.

Clara Vania

Applied Scientist, Amazon
Her research focuses on crowdsourcing, transfer learning, and multilingual NLU. Recently, she has been working on semi-automatic data collection for natural language inference and crowdsourcing methods for question answering.

Nikita Nangia

PhD student, New York University
Nikita’s work focuses on crowdsourcing methods and data creation for natural language understandingsoft. Her recent work explores using incentive structures to illicit creative examples. Nikita coorganized a tutorial on latent structure models for NLP at ACL 2019.

Maarten Sap

PhD student, University of Washington
His research focuses on endowing NLP systems with social intelligence and social commonsense, and understanding social inequality and bias in language. His substantial experience with crowdsourcing includes the collecting of the SOCIALIQA commonsense benchmark as well as the creation of knowledge graphs with inferential knowledge (ATOMIC, Social Bias Frames).

Mark Yatskar

Assistant Professor, University of Pennsylvania
His research focuses on the intersection of natural language processing and computer vision. Mark’s work has resulted in the creation of datasets such as imSitu, QuAC and WinoBias and recent research has focused on gender bias in visual recognition and coreference resolution.

Sam Bowman

Assistant Professor, New York University
Sam works on data creation, benchmarking, and model analysis for NLU and computational linguistics. Sam has had a substantial role in several NLU datasets, including SNLI, MNLI, XNLI, CoLA, and BLiMP, and his recent work has focused on experimentally evaluating methods for crowdsourced corpus construction.

Yoav Artzi

Associate Professor, Cornell University
Yoav's research focuses on learning expressive models for natural language understanding, most recently in situated interactive scenarios. Yoav led tutorials on semantic parsing in ACL 2013, EMNLP 2014 and AAAI 2015.