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Computational Linguistics and Information Processing

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= Fall 2010 =
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CLIP faculty teach courses across Computer Science, the College of Information, Linguistics, Neuroscience and Cognitive Science, and the Robert H. Smith School of Business. Topics include natural language processing, machine learning, computational psycholinguistics, information retrieval, data science, multilingual AI, trustworthy AI, language-model interpretation, and the social impacts of AI. Course offerings and instructors change by semester.


== Computational Linguistics I (Daume) ==  
== Fall 2026 (scheduled) ==
Fundamental methods in natural
language processing. Topics include: finite-state methods, context-free and extended context-free models
of syntax; parsing and semantic interpretation; n-gram and Hidden Markov models, part-of-speech
tagging; natural language applications such as machine translation, automatic summarization, and
question answering.


== Seminar in Computational Linguistics (Resnik) ==
* [https://app.testudo.umd.edu/soc/202608/INST/INST447 INST 447: Data Sources and Manipulation] (Ai)
This advanced seminar will focus on computational modeling of language, including cognitive/linguistic
* [https://app.testudo.umd.edu/soc/202608/INST/INST414 INST 414 / SDSI 414: Data Science Techniques] (Buntain)
aspects as well as practical language technology. Bayesian and information theoretic approaches will
* [https://app.testudo.umd.edu/soc/202608/INST/INST425 INST 425: AI for Text Analysis] (Mendelsohn)
figure prominently. The seminar will combine reviewing fundamental material, taking a reading-group
* [https://app.testudo.umd.edu/soc/202608/INST/INST423 INST 423 / INST 623: AI Adoption Clinic--Values-Centered AI for Community Organizations] (Frías-Martínez)
approach to key advanced papers, and (hopefully) bringing in guest speakers. Cross-disciplinary
* [https://app.testudo.umd.edu/soc/202608/BMGT/BMGT406 BMGT 406: AI Augmented App Development] (Raschid)
participation is strongly encouraged. ([http://umiacs.umd.edu/~resnik/ling848_fa2010/ Course Web page])
* [https://app.testudo.umd.edu/soc/202608/CMSC/CMSC422 CMSC 422: Introduction to Machine Learning] (Carpuat)
* [https://app.testudo.umd.edu/soc/202608/CMSC/CMSC470 CMSC 470: Introduction to Natural Language Processing] (Rudinger)
* [https://app.testudo.umd.edu/soc/202608/CMSC/CMSC723 CMSC 723 / INST 735 / LING 723: Natural Language Processing] (Iyyer)
* [https://app.testudo.umd.edu/soc/202608/CMSC/CMSC848A CMSC 848A: Trustworthy Machine Learning] (Daume)
* [https://app.testudo.umd.edu/soc/202608/CMSC/CMSC848R CMSC 848R: Language Model Interpretability] (Wiegreffe)
* [https://app.testudo.umd.edu/soc/202608/LING/LING849C LING 849C / CMSC 828F / NACS 728W: Computational Psycholinguistics] (Feldman, Resnik)


== Machine Learning (Getoor) ==
== Spring 2026 ==
Reviews and analyzes both traditional
symbol-processing methods and genetic algorithms as approaches to machine learning. (Neural network
learning methods are primarily covered in CMSC 727.) Topics include induction of decision trees and
rules, version spaces, candidate elimination algorithm, exemplar-based learning, genetic algorithms,
evolution under artificial selection of problem-solving algorithms, system assessment, comparative
studies, and related topics.


= Spring 2010 =
* [https://app.testudo.umd.edu/soc/202601/INST/INST878 INST 878: LLMs in Action--Transforming Information Research with GenAI] (Ai)
* [https://app.testudo.umd.edu/soc/202601/CMSC/CMSC848Q CMSC 848Q: Good AI Answers to Questions--How to Get Them and What Can Go Wrong] (Boyd-Graber)
* [https://app.testudo.umd.edu/soc/202601/INST/INST414 INST 414 / SDSI 414: Data Science Techniques] (Buntain)
* [https://app.testudo.umd.edu/soc/202601/CMSC/CMSC848T CMSC 848T: Frontiers in Multilingual AI] (Carpuat)
* [https://app.testudo.umd.edu/soc/202601/INST/INST664 INST 664: Transforming Unstructured Content with AI] (Mendelsohn)
* [https://app.testudo.umd.edu/soc/202601/INST/INST423 INST 423 / INST 623: AI Adoption Clinic--Values-Centered AI for Community Organizations] (Frías-Martínez)
* [https://app.testudo.umd.edu/soc/202601/LING/LING499R LING 499R: Understanding Language Understanding] (Resnik)
* [https://app.testudo.umd.edu/soc/202601/CMSC/CMSC470 CMSC 470: Introduction to Natural Language Processing] (Rudinger, Wiegreffe)


== Computational Linguistics II (Resnik) ==
== Spring 2022 ==
* [http://users.umiacs.umd.edu/~jbg/teaching/CMSC_848/ How and Why Artificial Intelligence Answers Questions] (Boyd-Graber)


This is the second semester in our graduate sequence in computational linguistics. Students are assumed to have taken the first semester (Ling723/CMSC723) or equivalent, and this class will provide foundations for advanced seminars in computational linguistics. Students are expected to be able to know how to program, and will exercise this ability periodically in homework assignments and/or projects.  The topics we'll cover are intended to get students up to speed on necessary background in order to understand and perform cutting-edge research in natural language processing, which requires a strong grounding in statistical NLP models and methods. Some of the topics are in the same areas as in Computational Linguistics I, but we will go deeper. As always, the syllabus is subject to revision; however, it will follow Manning and Schuetze's textbook relatively closely at least in early parts of the course.  ([http://www.umiacs.umd.edu/~resnik/ling773_sp2010/ Recent course Web page])
== Fall 2021 ==
* [http://users.umiacs.umd.edu/~jbg/teaching/CMSC_470/ Natural Language Processing] (Boyd-Graber)


== Cloud Computing (Boyd-Graber) ==
== Spring 2021 ==
* [https://sites.google.com/umd.edu/2021cl1webpage/ Computational Linguistics I] (Boyd-Graber/Resnik)
 
== Fall 2017 ==
 
* Computational Linguistics I (Carpuat)
* Multidisciplinary Seminar (Resnik)
* [http://www.umiacs.umd.edu/~jbg/teaching/CMSC_726/ Machine Learning] (Boyd-Graber)
 
== Spring 2017 ==
 
* Computational Linguistics II (Resnik)
 
* Computational Psycholinguistics (Feldman)
 
== Fall 2016 ==
 
* Computational Linguistics I (Carpuat)
* Reinforcement Learning (Daume)
* Computational Models of Human Parsing (Resnik)
 
== Spring 2016 ==
 
* Computational Linguistics II (Resnik)
* Machine Learning (Daume)
 
== Fall 2015 ==
 
* Computational Linguistics I (Carpuat)
* Computational Social Science (Resnik)
 
== Spring 2015 ==
 
* Computational Linguistics II (Resnik)
* Computational Psycholinguistics (Feldman)
* Multilingual Natural Language Processing (Carpuat)
 
== Fall 2014 ==
 
* Computational Linguistics I (Daume)
* [http://www.umiacs.umd.edu/~resnik/ling848_fa2014/ Semantics in Computational Linguistics] (Resnik)
 
== Spring 2014 ==
 
* [https://sites.google.com/site/linguisticprediction/ Linguistic Prediction] (Daume, Feldman, Lau)
* Computational Linguistics II (Resnik)
* [http://www.umiacs.umd.edu/~jbg/teaching/DATA_DIGGING/ Digging into Data] (Boyd-Graber)
 
== Fall 2013 ==
 
* Computational Linguistics I (Boyd-Graber)
* [http://www.umiacs.umd.edu/~resnik/ling848_fa2013/ Computational Social Science] (Resnik)
 
== Spring 2013 ==
 
* [https://sites.google.com/site/umdnpbayes/ Bayesian Nonparametrics] (Boyd-Graber, Daume, Feldman)
* Computational Linguistics II (Resnik)
* [http://www.umiacs.umd.edu/~jbg/teaching/DATA_DIGGING/ Digging into Data] (Boyd-Graber)
* Machine Learning (Daume)
* Cloud Computing (Lin)
* Computational Psycholinguistics (Feldman)
 
== Fall 2012 ==
 
* Computational Linguistics I (Daume)
 
== Spring 2012 ==
 
* [http://www.umiacs.umd.edu/~oard/teaching/708x/spring12/ E-Discovery] (Oard)
* [http://www.umiacs.umd.edu/~jbg/teaching/CMSC_773_2012/ Computational Linguistics II] (Boyd-Graber)
* Computational Psycholinguistics (Feldman)
 
== Fall 2011 ==
 
* [http://www.umiacs.umd.edu/~hollingk/classes/CompLing1-f11.html Computational Linguistics I] (Hollingshead)
* [http://www.umiacs.umd.edu/~hal/courses/2011F_MM/ Multilingual Modeling] (Daume)
 
== Spring 2011 ==
 
* Computational Linguistics II (Resnik)
* Computational Psycholinguistics (Feldman)
 
== Fall 2010 ==
 
* [http://www.umiacs.umd.edu/~hal/courses/2010F_CL1/ Computational Linguistics I] (Daume)
* [http://umiacs.umd.edu/~resnik/ling848_fa2010/ Seminar in Computational Linguistics] (Resnik)
* Machine Learning (Getoor)
 
== Spring 2010 ==
 
* [http://www.umiacs.umd.edu/~resnik/ling773_sp2010/ Computational Linguistics II] (Resnik)
* [http://www.umiacs.umd.edu/~jbg/teaching/INFM_718_2011/ Cloud Computing] (Boyd-Graber)

Latest revision as of 23:21, 27 July 2026

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CLIP faculty teach courses across Computer Science, the College of Information, Linguistics, Neuroscience and Cognitive Science, and the Robert H. Smith School of Business. Topics include natural language processing, machine learning, computational psycholinguistics, information retrieval, data science, multilingual AI, trustworthy AI, language-model interpretation, and the social impacts of AI. Course offerings and instructors change by semester.

Fall 2026 (scheduled)

Spring 2026

Spring 2022

Fall 2021

Spring 2021

Fall 2017

  • Computational Linguistics I (Carpuat)
  • Multidisciplinary Seminar (Resnik)
  • Machine Learning (Boyd-Graber)

Spring 2017

  • Computational Linguistics II (Resnik)
  • Computational Psycholinguistics (Feldman)

Fall 2016

  • Computational Linguistics I (Carpuat)
  • Reinforcement Learning (Daume)
  • Computational Models of Human Parsing (Resnik)

Spring 2016

  • Computational Linguistics II (Resnik)
  • Machine Learning (Daume)

Fall 2015

  • Computational Linguistics I (Carpuat)
  • Computational Social Science (Resnik)

Spring 2015

  • Computational Linguistics II (Resnik)
  • Computational Psycholinguistics (Feldman)
  • Multilingual Natural Language Processing (Carpuat)

Fall 2014

Spring 2014

Fall 2013

Spring 2013

  • Bayesian Nonparametrics (Boyd-Graber, Daume, Feldman)
  • Computational Linguistics II (Resnik)
  • Digging into Data (Boyd-Graber)
  • Machine Learning (Daume)
  • Cloud Computing (Lin)
  • Computational Psycholinguistics (Feldman)

Fall 2012

  • Computational Linguistics I (Daume)

Spring 2012

Fall 2011

Spring 2011

  • Computational Linguistics II (Resnik)
  • Computational Psycholinguistics (Feldman)

Fall 2010

Spring 2010

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