Machine Learning, AI, Computational Linguistics, and Information Retrieval
Developing methods that allow computers to perform learned tasks autonomously, creating practical solutions for human needs.
Research Projects
Enhancing Performance and Communication for Distributed Teams During Lunar Spacewalks
Principal Investigator(s): Susannah Paletz
Funder: NASA - Johnson Space Center Other Federal
Research Areas: Future of Work > Human-Computer Interaction > Machine Learning, AI, Computational Linguistics, and Information Retrieval
Principal Investigator(s): Susannah Paletz
Funder: NASA - Johnson Space Center Other Federal
Research Areas: Future of Work > Human-Computer Interaction > Machine Learning, AI, Computational Linguistics, and Information Retrieval
Harnessing Generative AI to Support Exploration and Discovery in Library and Archival Collection
Principal Investigator(s): Richard Marciano
Funder: 8/1/2024 - 4/9/2025 Institute of Museum and Library Services
Research Areas: Archival Science > Machine Learning, AI, Computational Linguistics, and Information Retrieval
Harnessing generative AI to support exploration and discovery in library and archival collections.
Principal Investigator(s): Richard Marciano
Funder: 8/1/2024 - 4/9/2025 Institute of Museum and Library Services
Research Areas: Archival Science > Machine Learning, AI, Computational Linguistics, and Information Retrieval
Harnessing generative AI to support exploration and discovery in library and archival collections.
Detecting and Mapping War-induced Damage to Agricultural Fields in Ukraine using Multi-Modal Remote Sensing Data
Principal Investigator(s): Sergii Skakun
Funder: NASA - Proposal Only Other Federal
Research Areas: Data Science, Analytics, and Visualization > Human-Computer Interaction > Machine Learning, AI, Computational Linguistics, and Information Retrieval > Smart Cities and Connected Communities > Social Networks, Online Communities, and Social Media
Principal Investigator(s): Sergii Skakun
Funder: NASA - Proposal Only Other Federal
Research Areas: Data Science, Analytics, and Visualization > Human-Computer Interaction > Machine Learning, AI, Computational Linguistics, and Information Retrieval > Smart Cities and Connected Communities > Social Networks, Online Communities, and Social Media
Faculty
Recent News
(Video) SoDa Symposium: “Prompt Engineering to Support AI Enabled Research”
Featuring Claire Kelley, senior data scientist and co-director for data science at Child Trends, and Trent D. Buskirk, professor at the …
New UMD research found that even when prompts using generative artificial intelligence lean toward positive emotion, such as joy or excitement, the images generated from these prompts tend to evoke fear as the dominant emotion. Illustration by Adobe Stock.
Maryland Today: How Images Reflect AI’s Dark ‘Spiral’ (ft. Cody Buntain)
INFO Assistant Professor Cody Buntain explores biases in generative AI, revealing how models often produce more negative content
Photo licensed by Adobe Stock