Computational Linguistics University at Buffalo

Overview

The Computational Linguistics programme at University at Buffalo is a collaborative Master of Science degree offered by the Department of Linguistics and the Department of Computer Science and Engineering. This interdisciplinary curriculum is specifically designed to equip students with the technical expertise required for the rapidly evolving human language technologies industry.

As a STEM-designated programme, it provides international students with eligibility for the STEM OPT extension. The course focuses on the intersection of human language and machine intelligence, ensuring graduates are prepared for technical roles in both research and commercial sectors.

Why Computational Linguistics at University at Buffalo?

Students benefit from the combined resources of two distinguished departments, fostering a unique environment for studying Natural Language Processing. The university maintains strong industry links, with students previously securing internships at prestigious organisations such as Comcast’s Applied AI group and the Natural Language Understanding Laboratory.

The institution is home to award-winning research initiatives, including the PROTO project which achieved third place in the global Alexa Prize Socialbot Grand Challenge. This research-active environment allows students to work alongside faculty who are leaders in artificial intelligence, geography, and political science.

Tuition Fee Breakdown

• International fee: USD 12870 per semester
• National fee: USD 12870 per semester
• Local fee: USD 5655 per semester

Visit the Fees and Funding section for a breakdown in your local currency.

Syllabus

The curriculum requires 36 credit hours and includes a mandatory capstone project involving significant programming. This project allows students to specialise in specific research methods or technical applications under faculty supervision.

Modules may include:

Linguistics

• Phonetics
• Syntax I
• Advanced Syntax
• Semantics I
• Semantics II
• Quantitative Methods in Linguistics
• Corpus Linguistics
• Head-driven Phrase-Structure Grammar
• Discourse pragmatics

Computer Science and Statistics

• Computer Science for non-majors I
• Information Retrieval
• Machine Learning
• Computational Linguistics
• Advanced Topics in Computational Linguistics
• Probability Theory for Data Science
• Basic Statistics for Social Sciences
• Analysis of Algorithms
• Deep Learning
• Reinforcement Learning
• NLP and Text Mining
• Pattern recognition
• Knowledge Representation
• Theory of Computation

Careers with Computational Linguistics

Graduates from this programme have a proven track record of securing high-level positions in the technology sector. Alumni have been recruited by global industry leaders including Meta, Amazon, Apple, and Google, often working as Language Engineers or Data Scientists.

Common career paths include roles such as NLP Research Engineer, Computational Linguist, and AI Scientist. Graduates also find success in specialised firms like Grammarly, Cohere, and BlueHalo, or continue their academic development in prestigious doctoral programmes across the globe.