Date: 29 Jun 2026 (Monday)
Time: 10:00 am - 12:00 nn
Venue: LI-1305, 1/F, Li Dak Sum Yip Yio Chin Academic Building, City University of Hong Kong
Speaker: Prof. Javier CHA
Language: English

Abstract

This presentation examines the impact transformer-based machine learning brings to the historian’s craft beyond familiar but limiting framings. These framings usually oscillate between dismissals of “AI slop” and unrealistic expectations of articles and monographs produced at the click of a button. Moving past this polarized discourse, the presentation asks how, in an era when historical research is conducted primarily through digital mediation, including the extensive digitized corpora now foundational in East Asian history, the transformer paradigm reshapes established digital historical practices.

Biography

Prof. Javier Cha is a digital historian and medievalist who uses technology to explore the East Asian world a millennium ago and also aims to prepare the historical profession for an era of data abundance and automation. His research spans the translation of primary sources in classical Chinese, machine-assisted historical methods, and experimental projects that address the challenges posed by big data and artificial intelligence in the humanities.

Cha is currently Assistant Professor of Digital Humanities at the University of Hong Kong. Previously, he was a founding member of the Leiden University Centre for Digital Humanities and taught at the interdisciplinary College of Liberal Studies at Seoul National University. He has secured multiple competitive grants and fellowships from the Hong Kong Research Grants Council, the Academy of Korean Studies, the Korea Foundation, the University of Hong Kong, Seoul National University, and the Social Sciences and Humanities Research Council of Canada. Most recently, he has been selected as one of the inaugural recipients of the Schmidt Sciences Humanities and AI Virtual Institute (HAVI) award for the “Playing Heaven” project, which aims to leverage transformer-based machine learning to develop sound computational methodologies for the intellectual and cultural history of early modern Neo-Confucianism.