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
MAITC Pilot A34 – MAITC Pilot A: Empowering Caregivers of Individuals with Cognitive Impairment to Make Safe Nonprescription Drug Decisions
Principal Investigator(s): Eun Kyoung Choe
Funder: National Institute on Aging (NIH) National Institutes of Health
Research Areas: Accessibility and Inclusive Design > Health Informatics > Human-Computer Interaction > Machine Learning, AI, Computational Linguistics, and Information Retrieval
This project introduces Aidara, an AI-powered digital health system designed to help caregivers make safer over-the-counter medication decisions for individuals with cognitive impairments. By using large language models to simplify and present drug information through multimodal formats- including text, speech, and visuals- Aidara aims to enhance understanding, reduce health risks, and improve self-guided medication management.
Principal Investigator(s): Eun Kyoung Choe
Funder: National Institute on Aging (NIH) National Institutes of Health
Research Areas: Accessibility and Inclusive Design > Health Informatics > Human-Computer Interaction > Machine Learning, AI, Computational Linguistics, and Information Retrieval
This project introduces Aidara, an AI-powered digital health system designed to help caregivers make safer over-the-counter medication decisions for individuals with cognitive impairments. By using large language models to simplify and present drug information through multimodal formats- including text, speech, and visuals- Aidara aims to enhance understanding, reduce health risks, and improve self-guided medication management.
CAREER: Self-Directed Human-LLM Coordination for Language Learning and Information Seeking
Principal Investigator(s): Ge Gao
Funder: National Science Foundation
Research Areas: Accessibility and Inclusive Design > Health Informatics > Human-Computer Interaction > Information Justice, Human Rights, and Technology Ethics > Machine Learning, AI, Computational Linguistics, and Information Retrieval > Youth Experience, Learning, and Digital Practices
This project uses AI-powered digital tutors to help individuals with limited majority-language proficiency improve their language skills for real-world information seeking. By enabling users to design personalized tutoring systems, the study advances language learning, AI literacy, and human-computer interaction.
Principal Investigator(s): Ge Gao
Funder: National Science Foundation
Research Areas: Accessibility and Inclusive Design > Health Informatics > Human-Computer Interaction > Information Justice, Human Rights, and Technology Ethics > Machine Learning, AI, Computational Linguistics, and Information Retrieval > Youth Experience, Learning, and Digital Practices
This project uses AI-powered digital tutors to help individuals with limited majority-language proficiency improve their language skills for real-world information seeking. By enabling users to design personalized tutoring systems, the study advances language learning, AI literacy, and human-computer interaction.
Human-Like Coaching for Home PT Exercises
Principal Investigator(s): Galina Madjaroff Reitz
Funder: Maryland Industrial Partnerships UMD Funded
Research Areas: Health Informatics > Human-Computer Interaction > Machine Learning, AI, Computational Linguistics, and Information Retrieval
Researchers are developing an AI-powered physical therapy coach that uses real-time motion tracking and personalized feedback to improve exercise adherence and outcomes. By simulating human-like interaction and emotional engagement, the project aims to make home-based rehabilitation more effective and accessible.
Principal Investigator(s): Galina Madjaroff Reitz
Funder: Maryland Industrial Partnerships UMD Funded
Research Areas: Health Informatics > Human-Computer Interaction > Machine Learning, AI, Computational Linguistics, and Information Retrieval
Researchers are developing an AI-powered physical therapy coach that uses real-time motion tracking and personalized feedback to improve exercise adherence and outcomes. By simulating human-like interaction and emotional engagement, the project aims to make home-based rehabilitation more effective and accessible.
Faculty
Staff
Recent News
Photo licensed by Adobe Stock via Road Red Runner
New International AI Safety Update Warns of Rapidly Evolving Risks
INFO’s Lee J. Tiedrich helps lead global efforts to address rapidly evolving AI risks in safety, cybersecurity and policy
UMD researchers and educators are working to improve AI and to understand how the technology is transforming the ways we teach, learn and prepare for an AI-driven world. (Illustration by iStock) via Maryland Today
Maryland Today: Spotlight on AI: UMD Transforms Every Stage of Education
INFO’s Wei Ai co-leads a UMD project using AI to enhance K–12 math instruction and teacher development
Chandler Colman ‘28 (left) and Samir Nazar ‘28 work on their final projects for “Knitting = Algorithms + Coding," one of 10 Maker Movement Approach to Computing classes offered this fall. The one-credit courses are designed to make it easier for students of all majors to learn about computing. (Photos by Dylan Singleton)