Litao Lin

Litao Lin (林立涛) is a researcher in computational humanities and knowledge organization, working on how places are recorded and given meaning in Chinese historical texts. His doctoral research at Nanjing University examines places mentioned in historical sources and how events and people attach significance to them, drawing on natural language processing, ontologies and linked data, and historical GIS (including CHGIS). He led a Jiangsu Province Postgraduate Research and Practice Innovation Program project (KYCX25_0124) on constructing place networks from multi-source historical documents and analyzing the influence of places within them. His work on aggregating thematic events in classical Chinese chronological histories was presented at iConference 2026 and published in Information Research.

From October 2025 to October 2026, he was a Fellow at the Institute for Quantitative Social Science (IQSS) at Harvard University, working on the China Biographical Database (CBDB) project under the guidance of Peter K. Bol. His work there centered on the Songshi jishi benmo: extracting biographical and office-holding data from the text, disambiguating historical persons, and linking event narratives to the people who took part in them.

Earlier, he contributed to SikuBERT and SikuGPT, pre-trained language models for classical Chinese, the latter published in the ACM Journal on Computing and Cultural Heritage (2024). He also co-organized EvaHan 2023, the first international evaluation of ancient Chinese machine translation, and was a visiting scholar at the TALOS AI4SSH program at the University of Crete in 2024.