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
An AI-Enhanced Colleague for Teachers: Developing and Studying an Innovative Platform for Efficient, Inclusive Middle-Grade Mathematics Lesson Planning
Principal Investigator(s):
Funder: National Science Foundation
Research Areas: Machine Learning, AI, Computational Linguistics, and Information Retrieval > Youth Experience, Learning, and Digital Practices
This project supports middle school math teachers by developing an AI-powered lesson planning tool that enhances efficiency, quality, and inclusivity. Integrating generative AI with research-based practices, it offers personalized guidance for creating effective lessons. The project also examines impacts on teacher stress, instructional effectiveness, and student learning outcomes.
Principal Investigator(s):
Funder: National Science Foundation
Research Areas: Machine Learning, AI, Computational Linguistics, and Information Retrieval > Youth Experience, Learning, and Digital Practices
This project supports middle school math teachers by developing an AI-powered lesson planning tool that enhances efficiency, quality, and inclusivity. Integrating generative AI with research-based practices, it offers personalized guidance for creating effective lessons. The project also examines impacts on teacher stress, instructional effectiveness, and student learning outcomes.
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.
Faculty
Recent News
Seven new UMD courses that delve into the role of artificial intelligence across art, public health, information science, psychology and more have received seed grants from the Artificial Intelligence Interdisciplinary Institute at Maryland (AIM). Illustration by iStock.
Maryland Today: 7 Proposals for AI-Focused Courses Awarded New Grants
INFO faculty Mega Subramaniam and Jessica Grimmer lead new UMD courses advancing AI literacy and creative innovation
(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.