Shijia Liu
(he/him/his)
PhD Student
Research Interests
- Natural language processing
- Digital humanities
- Natural language processing and information retrieval
Education
- MS in Computer Science, Johns Hopkins University
- MS in Electrical Engineering, Stanford University
- BS in Electrical Engineering, UCLA
- BS in Physics, UCLA
Biography
Shijia Liu is a doctoral student at the Khoury College of Computer Sciences at Northeastern University, advised by David Smith. His doctoral research, which he began in 2019 and expects to complete in 2025, focuses on natural language processing and artificial intelligence.
Liu integrates natural language processing and brain-computer interface technology. In particular, he builds better language models to assist people with locked-in syndrome; he also processes scanned historical books. While working on his master’s degree at Johns Hopkins University, Liu worked on quantifying the idiosyncrasies of Chinese classifiers.
Liu is affiliated with the NULab for Texts, Maps, and Networks.
Recent Publications
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Detecting de minimis Code-Switching in Historical German Books
Citation: Liu, Shijia, and David A. Smith. "Detecting de minimis Code-Switching in Historical German Books." Proceedings of the 28th International Conference on Computational Linguistics. 2020. -
Measuring the Similarity of Grammatical Gender Systems by Comparing Partitions
Citation: McCarthy, Arya D., et al. "Measuring the Similarity of Grammatical Gender Systems by Comparing Partitions." Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP). 2020. -
On the Idiosyncrasies of the Mandarin Chinese Classifier System
Citation: Shijia Liu, Hongyuan Mei, Adina Williams and Ryan Cotterell. 2019. On the Idiosyncrasies of the Mandarin Chinese Classifier System. In Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies