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(Computational Linguistics and Information Processing at Maryland)
 
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==Computational Linguistics and Information Processing at Maryland==
 
==Computational Linguistics and Information Processing at Maryland==
  
The CLIP laboratory at Maryland is interested in designing algorithms and building systems which allow computers to effectively and efficiently perform human language-related tasks. The lab is a part of the '''[http://umiacs.umd.edu/ University of Maryland Institute for Advanced Computer Studies (UMIACS)]''', and is composed of faculty, researchers, and students spanning multiple departments, including the '''[http://www.cs.umd.edu/ Department of Computer Science]''', '''[http://www.ling.umd.edu/ Department of Linguistics]''', '''[http://ischool.umd.edu/ iSchool]''', and the '''[http://www.rhsmith.umd.edu/ Robert H. Smith School of Business]'''.  
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The CLIP Laboratory at Maryland is engaged in designing algorithms and methods that allow computers to effectively and efficiently perform human language-related tasks, as well as using computational methods to improve our scientific understanding of the human capacity for language, and to explore heterogeneous datasets at scale. With faculty, researchers, and students spanning  
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the '''[http://www.cs.umd.edu/ Department of Computer Science]''', the '''[http://www.ling.umd.edu/ Department of Linguistics]''',
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the '''[http://ischool.umd.edu/ iSchool]''', and
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the '''[http://www.rhsmith.umd.edu/ Robert H. Smith School of Business]''',
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we are a group known not only for high quality research but also intellectual diversity and the strength of our collaborations.  
  
CLIP consists of two main entities: The Natural Language Group and the Database Group. The natural language group focuses on several areas of broadscale multilingual processing, e.g., [[Research#Machine_Translation|machine translation]], [[Research#Summarization|summarization]], scalable translingual document detection, and cross-language information retrieval. The database group focuses on architectures for wide area computation with heterogeneous information servers, e.g., scientific discovery from biomolecular data sources. Several language researchers in the CLIP lab are also affiliated with the '''[http://lamp.cfar.umd.edu/media.htm Language and Media Processing (LAMP) Laboratory]'''.
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We are part of the broader <span class="plainlinks">[http://languagescience.umd.edu/ language science]</span> center at Maryland, which integrates social and biological sciences with computer science and engineering. A number of language researchers in the CLIP lab are also affiliated with the  
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<span class="plainlinks">'''[https://nacs.umd.edu/ Neuroscience and Cognitive Science (NACS) program]'''</span>.  The lab is a part of the <span class="plainlinks">'''[http://umiacs.umd.edu/ University of Maryland Institute for Advanced Computer Studies (UMIACS)]'''</span>, and it is
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located in the Brendan Iribe Center for Computer Science and Engineering.  
  
== Course Offerings ==
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CLIP research covers major areas of computational research on language, including (but not limited to!)
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deep learning,
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human-in-the-loop machine learning,
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multilingual text processing and low-resource languages,
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[[Research#Machine_Translation|machine translation]], and
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computational psycholinguistics.
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We also study
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speech retrieval and
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cross-language information retrieval.
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Additional challenges include
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ranking and personalization,
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[[Research#Computational_Social_Science|computational social science]]
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NLP for mental health,
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data science for finance,
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data science for social good and e-discovery.
  
If you're interested in learning more, consider one of our courses:
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For further information about the CLIP Laboratory, feel free to contact its current director, '''[http://umiacs.umd.edu/~nhf/ Prof. Naomi Feldman]'''.
  
*[[Teaching]]
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Research in machine learning focuses on latent variable models of language, approximate inference, and how to make probabilistic models understandable to users.
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Data management research focuses on architectures for wide area computation with heterogeneous information servers, pattern  discovery from the annotated hyperlinked Web of life science resources, personalization and ranking and recommendation for social media, and event detection and monitoring.
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Latest revision as of 01:39, 1 October 2019

Computational Linguistics and Information Processing at Maryland

The CLIP Laboratory at Maryland is engaged in designing algorithms and methods that allow computers to effectively and efficiently perform human language-related tasks, as well as using computational methods to improve our scientific understanding of the human capacity for language, and to explore heterogeneous datasets at scale. With faculty, researchers, and students spanning the Department of Computer Science, the Department of Linguistics, the iSchool, and the Robert H. Smith School of Business, we are a group known not only for high quality research but also intellectual diversity and the strength of our collaborations.

We are part of the broader language science center at Maryland, which integrates social and biological sciences with computer science and engineering. A number of language researchers in the CLIP lab are also affiliated with the Neuroscience and Cognitive Science (NACS) program. The lab is a part of the University of Maryland Institute for Advanced Computer Studies (UMIACS), and it is located in the Brendan Iribe Center for Computer Science and Engineering.

CLIP research covers major areas of computational research on language, including (but not limited to!) deep learning, human-in-the-loop machine learning, multilingual text processing and low-resource languages, machine translation, and computational psycholinguistics. We also study speech retrieval and cross-language information retrieval. Additional challenges include ranking and personalization, computational social science NLP for mental health, data science for finance, data science for social good and e-discovery.

For further information about the CLIP Laboratory, feel free to contact its current director, Prof. Naomi Feldman.