Health Informatics
Improving the ability to access, understand, and make use of health information.
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.
P3 (Pregnancy and Postpartum/Preconception) EQUATE (Enhancing Access and Quality to Achieve Equitable Maternal and Infant Health) Network
Principal Investigator(s): Jasmine Garland McKinney
Funder: American Heart Association Other Non-Federal
Research Areas: Accessibility and Inclusive Design > Data Science, Analytics, and Visualization > Health Informatics > Information Justice, Human Rights, and Technology Ethics
This project validates the Prepartum Form for Evaluating Race-Related Psychological Stressors (PP-FERRPS)©, a screening tool designed to measure how race-related stressors affect Black perinatal women’s mental health. By refining this tool, the study aims to address gaps in traditional assessments and improve clinical support in maternal care.
Principal Investigator(s): Jasmine Garland McKinney
Funder: American Heart Association Other Non-Federal
Research Areas: Accessibility and Inclusive Design > Data Science, Analytics, and Visualization > Health Informatics > Information Justice, Human Rights, and Technology Ethics
This project validates the Prepartum Form for Evaluating Race-Related Psychological Stressors (PP-FERRPS)©, a screening tool designed to measure how race-related stressors affect Black perinatal women’s mental health. By refining this tool, the study aims to address gaps in traditional assessments and improve clinical support in maternal care.
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.
Faculty
Staff
Recent News
Photo licensed by Adobe Stock via Chalabala
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From leveraging AI for pedestrian safety to creating better touchscreen kiosks, the Maryland Initiative for Digital Accessibility brings together scientists across campus to transform existing and emerging tech for people with disabilities. (Illustration by iStock) Photo via Maryland Today.