2016–
Assistant Professor of Linguistics, Data Science & Computer Science
Co-PI, ML² Group & CILVR Lab
New York University
2011–2016
PhD Student
NLP Group, Department of Linguistics
Stanford University
Advisors: Chris Manning & Chris Potts
I study artificial neural network models for natural language understanding, with a focus on building high-quality training and evaluation data and on applying these models to scientific questions in syntax and semantics.
If we haven't been in contact previously, please look through this FAQ before emailing me. You can reach me at bowman@nyu.edu.
News
- My lab's software toolkit, jiant, just got a from-scratch rewrite, and we think it's a good starting point for most research on NLU, especially for the kinds of tasks that you see in benchmarks like GLUE, SuperGLUE, and XTREME. It builds on the popular Transformers and Datasets libraries.
- I joined the Department of Computer Science at NYU's Courant Institute as an associated faculty member, in addition to my primary appointment in Linguistics and Data Science.
- In a new AACL paper by Jason Phang et al., we've found impressive results from the use of English intermediate-task training on the cross-lingual transfer tasks in the XTREME benchmark.
- Alex Warstadt presented our work "Do self-supervised neural networks acquire a bias towards structural linguistic generalizations?" at CogSci this summer.
- I have a new EMNLP paper online covering some crowdsourcing methods design experiments I conducted with collaborators at Google in NYC.