Paul Hagstrom

Associate Professor of Linguistics
Director of Undergraduate Studies
Paul Hagstrom
Office phone: 617-353-6220
Fax: 617-358-4641
Office number: Linguistics 105
Office address: Linguistics Department, 621 Commonwealth Ave.
Boston, MA 02215
Office hours: Spring 2020: MRF 12-1; or by appointment.
Note: Thursday office hours will be 11-12 instead of 12-1 on 1/23, 1/30, 2/6, and 2/14.

BA, Physics and Mathematics, Carleton College
PhD, Linguistics, Massachusetts Institute of Technology

Professor Hagstrom's research interests are in syntax, semantics, and language acquisition.


Spring 2020

Course number Course title Section Instructor Days Time Room

CAS LX 422

Intermediate Syntax: Modeling Syntactic Knowledge

A1 Hagstrom TR 2-3:15 CAS 208
Using linguistic data drawn from a wide variety of languages, students develop a precise model of syntactic knowledge through evaluation of hypotheses and arguments. Exploration of major discoveries and phenomena from the linguistic literature. [Prereq: CAS LX 321 / GRS LX 621 Syntax: Introduction to Sentential Structure (or CAS LX 522) or consent of instructor.]
[Meets with GRS LX 722]

CAS LX 496

Computational Linguistics

A1 Hagstrom T 3:30-6:15 EPIC 205
Introduction to computational techniques to explore linguistic models and test empirical claims. Serves as an introduction to concepts, algorithms, data structures, and tool libraries. Topics include tagging and classification, parsing models, meaning representation, corpus creation, information extraction. [Prereq: Prereq: CAS LX 250 and CAS CS 112, or consent of instructor]
[Meets with GRS LX 796]
Students who have already taken CAS LX 394/GRS LX 694 are not eligible to take this course.
  • Carries divisional credit for Math and Computer Science in CAS. Note, however, that courses taken toward a major or minor in Linguistics (Humanities) cannot be used for credit toward the Divisional Studies Requirement in a different division.
  • This course fulfills a single unit in each of the following BU Hub areas:
    • Quantitative Reasoning II
    • Research & Information Literacy