Summary
Yiming Liang is a postdoctoral researcher based in Paris specializing in corpus and computational linguistics with a strong focus on language evolution, information theory, and efficiency in communication. With two years of post-PhD research experience and prior industry roles in NLP and data management, he builds end-to-end pipelines—from PDF/web collection and normalization to automatic annotation, parsing, and database transformation—often automating quality control with Python. He has contributed as a core developer of a Middle Dutch Treebank and applied information-theoretic metrics to trace language change, bridging historical linguistics and modern ML methods such as fine-tuning GPT for spoken French. Comfortable supervising interns and collaborating with annotators and project managers, he combines rigorous academic publication experience with practical production skills in data standardization and annotation consistency. A bilingual background in French and Chinese and an unusual mix of translation experience and ERC-funded research give him a rare angle on cross-linguistic phenomena and data-driven language modeling.
1 year of coding experience
Doctor of Philosophy - PhD, Corpus linguistics, computational linguistics, theoretical syntax, Doctor of Philosophy - PhD, Corpus linguistics, computational linguistics, theoretical syntax at Université de Paris
Exchange Year, French Linguistics, Exchange Year, French Linguistics at Université Paris-Sorbonne
Master's degree, General linguistics, experimental linguistics, M2: 17/20, Mention très bien | M1: 16/20, Mention très bien, Master's degree, General linguistics, experimental linguistics, M2: 17/20, Mention très bien | M1: 16/20, Mention très bien at Université Paris Diderot
Bachelor's degree, French language and literature, Bachelor's degree, French language and literature at Beijing Foreign Studies University
French, English, Chinese, Chinese, Thai