Abhilasha Ravichander is a postdoctoral researcher at the Allen Institute for AI. She received her PhD in Artificial Intelligence from Carnegie Mellon University in December 2022, and her MS from Carnegie Mellon University in 2018. Abhilasha is broadly interested in Natural Language Processing (NLP) and her research addresses the robustness and interpretability of NLP systems, with a focus on analyzing, evaluating, and improving models and datasets. Her work has been presented at several top NLP conferences, receiving a best paper award at the SoCalNLP 2022 symposium and an Area Chair Favorite Paper prize at COLING 2018. She was also selected as a “Rising Star in Data Science” by the University of Chicago in 2021, and a "Rising Star in EECS" in 2022, by the University of Texas at Austin. During her PhD, she served as co-chair of the socio-cultural inclusion committee for NAACL 2022, area chair at EMNLP 2022, was named an outstanding reviewer at ACL 2020 and EMNLP 2020, and co-organized the ‘NLP WIth Friends’ seminar series.
Privacy plays a crucial role in preserving user autonomy. While internet users care about data privacy, it has become increasingly difficult to understand exactly how information is collected, shared and used by various entities. In this talk, we will examine the privacy challenges involved in building Natural Language Processing (NLP) systems, as well as the potential benefits NLP...