I am a recent MA graduate in Applied Linguistics from the University of Saskatchewan. My main research interests are in natural language processing (NLP), corpus linguistics, and computational social science. I employ both computational and linguistic approaches to studying the properties of languages and their linguistic and social meanings inferred from actual language use in large-scale linguistic corpora. I am also highly interested in how neural networks encode linguistic knowledge and "learn" human languages.

Inspired by Andrew Ng, I believe in the prospect of data-centric AI (versus model-centric AI). With my research, I aim to leverage both linguistic domain knowledge and learning algorithms to help train more robust NLP models with data that is either much smaller in size or can be obtained with much less manual efforts. Only in this way can we advance computational linguistics to understudied text and language domains and bring more practical values to the real world.


I was born and raised in Fuqing, a small southeastern city of China. From 2015 to 2019, I studied at Hunan University for my bachelor's degree. Majoring in Chinese Language and Literature, I found my passion for linguistics in the first year of university and managed to undertake a two-year funded project on Chinese grammar and a three-month psycholinguistic internship in Canada. Besides literature- & linguistics- related research, I also spent time doing research in law, history, social science, and a bit of philosophy.

From 2019 to 2021, I studied at the University of Saskatchewan, majoring in Applied Linguistics. I taught myself programming and computational linguistics and focused on quantitative and data-driven analysis of language use in transcribed linguistic corpora. From purely rule-based programming, exemplified by extensive regular expressions for syntactic parsing, text extraction, and corpus annotation, I steadily became fluent in building NLP models with statistical machine learning and deep learning. As I am new to this area, I welcome any like-minded people to reach out!


My full CV.



Deep Learning

Text Processing

Web Scraping

  • Google Scholar Analyzer : Auto-aggregating academic profiles of researchers on Google Scholar.
  • YouTube Info Collector : An interface to scrape information (video titles, post dates, view counts, like counts, and comments etc.) from YouTube videos based on queries, video links, or channel links.