Paul Vierthaler

Paul Vierthaler serves as Assistant Professor of Chinese Literature and Interdisciplinary Data Science at Princeton University's Department of East Asian Studies. His dual expertise bridges traditional Chinese literary scholarship with cutting-edge computational methodologies, positioning him at the forefront of digital humanities research in East Asian studies.

His research focuses on late Imperial Chinese literature (1550-1799), particularly historical narratives in unofficial genres including novels, dramas, and unofficial histories. Vierthaler specializes in applying digital humanities techniques such as natural language processing, stylometry, social network analysis, and GIS to analyze large-scale Chinese textual corpora. His methodological innovations include adapting bioinformatics algorithms like BLAST for intertextuality detection in Chinese texts and developing machine learning models for authorship attribution and genre classification.

Vierthaler's publication trends reveal a consistent focus on computational approaches to Chinese literary scholarship, with particular emphasis on the Jin Ping Mei (Plum in the Golden Vase) and broader late Ming/Qing textual production. His work demonstrates how digital methods can uncover patterns in textual borrowing, stylistic evolution, and historical information flow across thousands of pre-modern Chinese documents.

Vierthaler actively contributes to digital infrastructure development for Chinese studies through projects like MARKUS and his bibliographic graph database using Neo4j. His research has been presented at major international conferences including Pacific Neighborhood Consortium, European Chinese Digital Humanities Conference, and Association for Asian Studies meetings.