teaching
instructor of record
- Spring 2026 - LING 471: Computational Methods for Linguists (scheduled)
teaching assistant
- Autumn 2025 - LING 570: Shallow Processing Techniques for Natural Language Processing
- Autumn 2024 - LING 570: Shallow Processing Techniques for Natural Language Processing
- Winter 2024 - LING 572: Advanced Statistical Methods in Natural Language Processing
- Autumn 2023 - LING 571: Deep Processing Techniques for Natural Language Processing
- Spring 2023 - LING 471: Computational Methods for Linguists
Guest lecture on Statistics Basics for NLP - Spring 2022 - LING 200: Introduction to Linguistics
Teaching two 1-hour 30-person sessions twice weekly - Autumn 2021 - LING 200: Introduction to Linguistics
Teaching two 1-hour 30-person sessions twice weekly
grader
- Winter 2022 - LING 461: Syntax I
other guest lectures & invited talks
- Spring 2025 - MELC 268: Silk Road and Globalization
Languages of the Silk Road - Winter 2024 - MELC 269: Music Cultures of the Silk Road
Tibetan Music
course descriptions
LING 471: Computational Methods for Linguists
Focuses on how computational methods and tools can be applied in linguistics, emphasizing the basics of programming and general technical versatility skills needed for programming tasks. Assignments are organized around linguistics or linguistically annotated data. Students learn to write Python programs, discuss what counts as data in computational linguistics, connect linguistic theory to computational method choice, and reflect on the ethical and social implications of data use.
LING 570: Shallow Processing Techniques for Natural Language Processing
Covers techniques and algorithms for associating relatively surface-level structures and information with natural language corpora, including POS tagging, morphological analysis, preprocessing/segmentation, named-entity recognition, chunk parsing, and word-sense disambiguation. Examines linguistic resources that can be leveraged for these tasks (e.g., WordNet).
LING 571: Deep Processing Techniques for Natural Language Processing
Covers algorithms for associating deep or elaborated linguistic structures with naturally occurring data, covering parsing, semantics, and discourse.
LING 572: Advanced Statistical Methods in Natural Language Processing
Covers several important machine learning algorithms for natural language processing including decision tree, kNN, Naive Bayes, support vector machine, maximum entropy / multinomial logistic regression, conditional random fields, and neural networks. Students implement many of the algorithms and apply these algorithms to some NLP tasks.
LING 200: Introduction to Linguistics
Introduces language as the fundamental characteristic of the human species, exploring the diversity and complexity of human languages. Topics include phonological and grammatical analysis, dimensions of language use, language acquisition, and historical language change.