Published several papers, including 'Clustering Running Titles to Understand the Printing of Early Modern Books' (ICDAR 2024) and 'Temporal Adaptation of LLM Text Classification Models Under Changing Label Sets' (EMNLP 2023). Recipient of an NSF Graduate Research Fellowship. Team won first prize in the Persona and Influence category of NSIN's Cyber Innovators Challenge.
Research Experience
Working in the Berg Lab, focusing on natural language processing and machine learning, especially in the digital humanities. At CMU, worked on machine translation with applications to assistive technology for simultaneous interpreters. A few years ago, contributed to a project on multimodal analysis of Parkinson's disease at the Third Frederick Jelinek Memorial Workshop at JHU.
Education
Pursuing a Ph.D. at the University of California, San Diego, advised by Taylor Berg-Kirkpatrick; received a Master's degree from Carnegie Mellon University, advised by Graham Neubig; Bachelor's degree from UC Irvine.
Background
A graduate student in Computer Science and Engineering, with research interests in natural language processing and machine learning, particularly in the digital humanities. Currently focused on NLP for historical documents, such as early modern books and manuscript collections.