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
A farmer tends crops in Uganda, an area where bias in AI algorithms monitoring global crop health might misinterpret data due to a lack of knowledge of local growing methods. Photo by Nuno Almeida, Dreamstime.com
UMD Co-leads $750K NSF, Amazon Project to Tackle AI Bias in Mapping
INFO College's Dr. Sergii Skakun will play a key role in building the system that could enable fairer, safer decisions on resource distribution
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.