Human-Computer Interaction
Developing advanced user-focused interfaces and design methods that are shaping the future of technology.
Research Projects
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.
Piloting Lab Discourse Graphs for Sustainable Research Communication
Principal Investigator(s): Joel Chan
Funder: The Navigation Fund; Chan Zuckerberg Initiative (CZI) Other Non-Federal
Research Areas: Data Science, Analytics, and Visualization > Human-Computer Interaction > Machine Learning, AI, Computational Linguistics, and Information Retrieval
This project develops tooling for Discourse Graphs, a system enabling researchers to share and build on evidence-based research. Supported by $1.35M from the Chan-Zuckerberg Initiative and Navigation Fund, it collaborates with a PI at UW to enhance research workflows and open-science practices.
Principal Investigator(s): Joel Chan
Funder: The Navigation Fund; Chan Zuckerberg Initiative (CZI) Other Non-Federal
Research Areas: Data Science, Analytics, and Visualization > Human-Computer Interaction > Machine Learning, AI, Computational Linguistics, and Information Retrieval
This project develops tooling for Discourse Graphs, a system enabling researchers to share and build on evidence-based research. Supported by $1.35M from the Chan-Zuckerberg Initiative and Navigation Fund, it collaborates with a PI at UW to enhance research workflows and open-science practices.
Collaborative Research: ER2: Developing Educational Resources for the Ethical Use of Pervasive Data
Principal Investigator(s): Jessica Vitak
Funder: National Science Foundation
Research Areas: Data Privacy and Sociotechnical Cybersecurity > Human-Computer Interaction > Information Justice, Human Rights, and Technology Ethics > Machine Learning, AI, Computational Linguistics, and Information Retrieval > Social Networks, Online Communities, and Social Media
This project develops educational resources and training to promote ethical practices in the collection, storage, and analysis of pervasive data from digital platforms. By creating case studies, interactive modules, and “train the trainer” programs, it aims to enhance responsible research practices among computing students and early-career researchers.
Principal Investigator(s): Jessica Vitak
Funder: National Science Foundation
Research Areas: Data Privacy and Sociotechnical Cybersecurity > Human-Computer Interaction > Information Justice, Human Rights, and Technology Ethics > Machine Learning, AI, Computational Linguistics, and Information Retrieval > Social Networks, Online Communities, and Social Media
This project develops educational resources and training to promote ethical practices in the collection, storage, and analysis of pervasive data from digital platforms. By creating case studies, interactive modules, and “train the trainer” programs, it aims to enhance responsible research practices among computing students and early-career researchers.
Faculty
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