Swabha Swayamdipta
Postdoctoral Investigator • MOSAIC • Allen Institute for AI
My research focuses on studying biases in datasets and models. Good biases, such as structural inductive biases help language understanding - check out my PhD thesis on these. But biases can be undesirable, e.g. spurious correlations commonly found in crowd-sourced, large-scale datasets due to annotation artifacts, or social prejudices of human annotators and task designers (coming soon!).
Previously…
I obtained my PhD from Carnegie Mellon University in May 2019, where I was advised by Noah Smith and Chris Dyer. During most of my PhD I was a visiting student at the University of Washington in Seattle.
Update I am looking for academic positions in Winter / Spring 2021!
news
| Nov 2, 2020 | Was delighted to be an invited speaker for Responsible AI at the Microsoft E+D Product Leaders Conference. |
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| Sep 22, 2020 | Preprint for EMNLP acceptance Dataset Cartography is now available on ArXiv. Camera-ready version and code coming soon! |
| Sep 15, 2020 | Paper titled Dataset Cartography: Mapping and Diagnosing Datasets with Training Dynamics is now accepted to the Proceedings of EMNLP, and GDaug is accepted to Findings of EMNLP. |
| Aug 13, 2020 | Completed one year as a postdoctoral investigator at AI2! |
| Jul 8, 2020 | Our paper Don’t Stop Pretraining: Adapt Language Models to Domains and Tasks received an Honorable Mention Award at ACL 2020! |