Computational Linguistics, Machine Learning, and Information Retrieval
Developing methods that allow computers to perform learned tasks autonomously, creating practical solutions for human needs.
Research Projects
When Does Encouraging Diverse Initial Solutions Lead to Better Final Solutions?
Principal Investigator(s): Joel Chan
Funder: National Science Foundation
Research Areas: Computational Linguistics, Machine Learning, and Information Retrieval > Data Science, Analytics, and Visualization
Designing high-performing engineering systems--for example, fuel-efficient aircraft, medical devices, new manufacturing and agricultural equipment--requires searching for high-quality solutions among many possible options.
Principal Investigator(s): Joel Chan
Funder: National Science Foundation
Research Areas: Computational Linguistics, Machine Learning, and Information Retrieval > Data Science, Analytics, and Visualization
Designing high-performing engineering systems--for example, fuel-efficient aircraft, medical devices, new manufacturing and agricultural equipment--requires searching for high-quality solutions among many possible options.
UMD-ARL Alliance for Additive Manufacturing Science
Principal Investigator(s): Richard Marciano
Funder: US Army Research Office
Research Areas: Computational Linguistics, Machine Learning, and Information Retrieval > Future of Work > Library and Information Science
Principal Investigator(s): Richard Marciano
Funder: US Army Research Office
Research Areas: Computational Linguistics, Machine Learning, and Information Retrieval > Future of Work > Library and Information Science
Center For Excellence in Human Language Technology
Principal Investigator(s): Douglas W. Oard
Funder: Johns Hopkins University Other
Research Areas: Computational Linguistics, Machine Learning, and Information Retrieval > Human-Computer Interaction
Principal Investigator(s): Douglas W. Oard
Funder: Johns Hopkins University Other
Research Areas: Computational Linguistics, Machine Learning, and Information Retrieval > Human-Computer Interaction
Faculty
Staff
Recent News
Photo by Chris Curry on Unsplash
(Video) Search Mastery Speaker Series: Manchester vs. Cranfield
A discussion about why we answer questions, and how a new paradigm can justify crafting search queries that go beyond information seeking.
Can a Strategy Game Help AI Learn to Spot Scammers?
iSchool Associate Professor, Dr. Jordan Boyd-Graber, joins team of researchers awarded $1M to support U.S. Military’s cybersecurity fight.
Image by Maria Herd