Human-Computer Interaction
Developing advanced user-focused interfaces and design methods that are shaping the future of technology.
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.
Postdoctoral Fellowship: STEMEdIPRF: SAGE4ICE: Student Analogy Generation Empowerment for Computing Education
Principal Investigator(s):
Funder: National Science Foundation
Research Areas: Accessibility and Inclusive Design > Data Science, Analytics, and Visualization > Future of Work > Human-Computer Interaction > Youth Experience, Learning, and Digital Practices
This project develops classroom activities, digital scaffolding tools, and an online library to guide students in creating effective analogies for learning computing concepts. By improving comprehension and persistence in introductory courses, the project aims to broaden participation and strengthen the pipeline of future computing professionals.
Principal Investigator(s):
Funder: National Science Foundation
Research Areas: Accessibility and Inclusive Design > Data Science, Analytics, and Visualization > Future of Work > Human-Computer Interaction > Youth Experience, Learning, and Digital Practices
This project develops classroom activities, digital scaffolding tools, and an online library to guide students in creating effective analogies for learning computing concepts. By improving comprehension and persistence in introductory courses, the project aims to broaden participation and strengthen the pipeline of future computing professionals.
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
Recent News
Photo courtesy of Maryland Global
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Photo licensed by Adobe Stock via Ashi
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