Human-Computer Interaction
Developing advanced user-focused interfaces and design methods that are shaping the future of technology.
Research Projects
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.
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
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