|Position: Assistant Professor
Office: TCL 304
E-mail: [email protected]
- Ph.D. University of Massachusetts Amherst, 2021
- M.S. University of Massachusetts Amherst, 2020
- B.A. Lewis & Clark College, 2015
- Natural language processing
- Computational social science
- Machine learning
- Causal inference
- Data science
Prior to Williams, Katherine (Katie) Keith was a Postdoctoral Young Investigator with the Semantic Scholar team at the Allen Institute for Artificial Intelligence. She graduated with a PhD from the College of Information and Computer Sciences at the University of Massachusetts Amherst where she was advised by Brendan O’Connor. Her research interests are at the intersection of natural language processing, computational social science, and causal inference. In the past, she co-organized the First Workshop on Causal Inference and NLP, hosted the podcast Diaries of Social Data Research, and co-organized the first NLP+CSS 201 Online Tutorial Series. She is a recipient of a Bloomberg Data Science PhD fellowship.
Katie’s research is in the domain of social data science, answering questions about human behavior through quantitative analysis of large-scale data. She’s interested in adapting methods from natural language processing to the needs of computational social scientists. Most recently, her work has examined the challenges of using text as high-dimensional causal confounders. She primarily publishes in conference proceedings of the Association for Computational Linguistics (ACL, EMNLP, and NAACL).