I am interested in evaluating and improving the robustness of (multilingual) NLP systems. My work spans (causal) interpretability methods, pre-training and meta-learning methods, and evaluating the linguistic abilities and inductive biases of pre-trained language models. I'm supported in my PhD studies by a National Science Foundation (NSF) Graduate Research Fellowship.

I completed my B.S. in computer science and B.S. in linguistics at the University of Kentucky (UK), where I was a Gaines Fellow and Patterson Scholar. My thesis, which focused on neural machine translation for low-resource French dialects, was advised by Ramakanth Kavuluru and Mark Richard Lauersdorf.

Organizing the BabyLM Shared Task

Invited talks at Bar-Ilan University and the Technion

Presented a paper at CoNLL

Interned at Meta Research in Menlo Park

Presented two papers at ACL 2022 (one main conference, one in Findings)

Invited talk at the National Research Council of Canada

Joined NYU for the academic year as a visiting researcher

Presented a paper at ACL

Presented a paper at NAACL

Defended my thesis proposal! ABD!

Joined Amazon as an applied scientist for the summer

Invited talk at Google

Invited talk at Mila