Research Projects
Filtered by: Human-Computer Interaction
Achieving Optimal Motor Function in Stroke Survivors via a Human-Centered Approach to Design an mHealth Platform
Principal Investigator(s): Eun Kyoung Choe
Funders: National Institutes of Health
Research Areas: Accessibility and Inclusive Design Health Informatics Human-Computer Interaction
Stroke rehabilitation, mHealth, Human-Computer Interaction
Partners: University of Massachusetts Amherst, Spaulding Rehabilitation Hospital, Formsense
Principal Investigator(s): Eun Kyoung Choe
Funders: National Institutes of Health
Research Areas: Accessibility and Inclusive Design Health Informatics Human-Computer Interaction
Stroke rehabilitation, mHealth, Human-Computer Interaction
Partners: University of Massachusetts Amherst, Spaulding Rehabilitation Hospital, Formsense
Campus Computation Center: Support, Enrichment & Computing Identity Development to Boost STEM Success
Principal Investigator(s): Katherine Izsak Ron Padrón Vedat G. Diker Bill Kules beth bonsignore
Funders: DoD-Navy
Research Areas: Accessibility and Inclusive Design Human-Computer Interaction Youth Experience, Learning, and Digital Practices
The project focuses on several research areas, including Accessibility and Inclusive Design, Human-Computer Interaction, and Youth Experience, Learning, and Digital Practices.
Principal Investigator(s): Katherine Izsak Ron Padrón Vedat G. Diker Bill Kules beth bonsignore
Funders: DoD-Navy
Research Areas: Accessibility and Inclusive Design Human-Computer Interaction Youth Experience, Learning, and Digital Practices
The project focuses on several research areas, including Accessibility and Inclusive Design, Human-Computer Interaction, and Youth Experience, Learning, and Digital Practices.
CAREER: Advancing Remote Collaboration: Inclusive Design for People with Dementia
Principal Investigator(s): Amanda Lazar
Funders: National Science Foundation
Research Areas: Health Informatics Human-Computer Interaction Social Networks, Online Communities, and Social Media
Technology increasingly provides opportunities to interact remotely with others. People with cognitive impairment can be excluded from these opportunities when technology is not designed with their needs, preferences, and abilities in mind.
Principal Investigator(s): Amanda Lazar
Funders: National Science Foundation
Research Areas: Health Informatics Human-Computer Interaction Social Networks, Online Communities, and Social Media
Technology increasingly provides opportunities to interact remotely with others. People with cognitive impairment can be excluded from these opportunities when technology is not designed with their needs, preferences, and abilities in mind.
CAREER: API Can Code: Situating Computational Learning Opportunities in the Digital Lives of Students
Principal Investigator(s): David Weintrop
Funders: National Science Foundation
Research Areas: Data Science, Analytics, and Visualization Human-Computer Interaction Youth Experience, Learning, and Digital Practices
This project develops and studies a high school data science curriculum that integrates programming and real-world datasets to engage students in exploring their own questions and interests. Designed in partnership with an urban school district, the research focuses on expanding access to computing for populations historically excluded from the field.
Principal Investigator(s): David Weintrop
Funders: National Science Foundation
Research Areas: Data Science, Analytics, and Visualization Human-Computer Interaction Youth Experience, Learning, and Digital Practices
This project develops and studies a high school data science curriculum that integrates programming and real-world datasets to engage students in exploring their own questions and interests. Designed in partnership with an urban school district, the research focuses on expanding access to computing for populations historically excluded from the field.
CAREER: Self-Directed Human-LLM Coordination for Language Learning and Information Seeking
Principal Investigator(s): Ge Gao
Funders: 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
Funders: 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.
CAREER: Socio-Algorithmic Foundations of Trustworthy Recommendations
Principal Investigator(s): Giovanni Luca Ciampaglia
Funders: National Science Foundation
Research Areas: Data Science, Analytics, and Visualization Human-Computer Interaction Social Networks, Online Communities, and Social Media
This project investigates how incorporating audience diversity into content recommendation systems can improve trustworthiness and news quality. It will develop new algorithms, evaluate re-ranking methods, and test impacts on the information diets of news consumers, particularly older audiences.
Principal Investigator(s): Giovanni Luca Ciampaglia
Funders: National Science Foundation
Research Areas: Data Science, Analytics, and Visualization Human-Computer Interaction Social Networks, Online Communities, and Social Media
This project investigates how incorporating audience diversity into content recommendation systems can improve trustworthiness and news quality. It will develop new algorithms, evaluate re-ranking methods, and test impacts on the information diets of news consumers, particularly older audiences.
CHS: Medium: Collaborative Research: Teachable Activity Trackers for Older Adults
Principal Investigator(s): Eun Kyoung Choe
Funders: National Science Foundation
Research Areas: Accessibility and Inclusive Design Data Science, Analytics, and Visualization Health Informatics Human-Computer Interaction
Pushing the boundaries of how personal tracking devices, such as smart watches, can better support older adults---by identifying what health/activities data would be most useful for older adults if tracked, how to collect/track this data, and utilizing this information to develop a new personalized, multimodal activity tracker.
Principal Investigator(s): Eun Kyoung Choe
Funders: National Science Foundation
Research Areas: Accessibility and Inclusive Design Data Science, Analytics, and Visualization Health Informatics Human-Computer Interaction
Pushing the boundaries of how personal tracking devices, such as smart watches, can better support older adults---by identifying what health/activities data would be most useful for older adults if tracked, how to collect/track this data, and utilizing this information to develop a new personalized, multimodal activity tracker.
Collaborative Research: ER2: Developing Educational Resources for the Ethical Use of Pervasive Data
Principal Investigator(s): Jessica Vitak
Funders: 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
Funders: 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.
DataGOAT – Building Counter Structures to Combat Systemic Racism in STEM Education & Sport Through Data Literacy
Principal Investigator(s): Tamara Clegg
Funders: National Science Foundation
Research Areas: Data Science, Analytics, and Visualization Human-Computer Interaction Information Justice, Human Rights, and Technology Ethics Youth Experience, Learning, and Digital Practices
The DataGOAT project integrates data science education with college athletics to promote STEM engagement and racial equity, particularly for Black male athletes. By creating coursework, internships, and technical tools, the project empowers athletes with critical data literacy while challenging stereotypes and linking athletic data practices to meaningful academic and career pathways.
Principal Investigator(s): Tamara Clegg
Funders: National Science Foundation
Research Areas: Data Science, Analytics, and Visualization Human-Computer Interaction Information Justice, Human Rights, and Technology Ethics Youth Experience, Learning, and Digital Practices
The DataGOAT project integrates data science education with college athletics to promote STEM engagement and racial equity, particularly for Black male athletes. By creating coursework, internships, and technical tools, the project empowers athletes with critical data literacy while challenging stereotypes and linking athletic data practices to meaningful academic and career pathways.
Designing AI-powered DIY Communication Tools with AAC users
Principal Investigator(s): Stephanie Valencia²
Funders: Google Corporation
Research Areas: Accessibility and Inclusive Design Human-Computer Interaction Machine Learning, AI, Computational Linguistics, and Information Retrieval
This Google Research Scholar-funded project designs AI-powered DIY communication tools to enhance accessibility for augmentative and alternative communication (AAC) users.
Principal Investigator(s): Stephanie Valencia²
Funders: Google Corporation
Research Areas: Accessibility and Inclusive Design Human-Computer Interaction Machine Learning, AI, Computational Linguistics, and Information Retrieval
This Google Research Scholar-funded project designs AI-powered DIY communication tools to enhance accessibility for augmentative and alternative communication (AAC) users.
Detecting and Mapping War-induced Damage to Agricultural Fields in Ukraine using Multi-Modal Remote Sensing Data
Principal Investigator(s): Sergii Skakun
Funders: NASA Other Federal
Research Areas: Data Science, Analytics, and Visualization Human-Computer Interaction Machine Learning, AI, Computational Linguistics, and Information Retrieval Smart Cities and Connected Communities Social Networks, Online Communities, and Social Media
This project advances remote sensing methods to map war-induced damage to Ukraine’s agricultural fields using infrared and visible spectrum satellite data. By developing deep-learning and data fusion techniques, the research will detect artillery craters, burned areas, and abandoned fields to assess the war’s impact on agriculture at scale.
Principal Investigator(s): Sergii Skakun
Funders: NASA Other Federal
Research Areas: Data Science, Analytics, and Visualization Human-Computer Interaction Machine Learning, AI, Computational Linguistics, and Information Retrieval Smart Cities and Connected Communities Social Networks, Online Communities, and Social Media
This project advances remote sensing methods to map war-induced damage to Ukraine’s agricultural fields using infrared and visible spectrum satellite data. By developing deep-learning and data fusion techniques, the research will detect artillery craters, burned areas, and abandoned fields to assess the war’s impact on agriculture at scale.
Developing and Investigating Data Science Interventions Connected to University Athletics to Address Systemic Racism in Undergraduate STEM Education (better known as DataGOAT)
Principal Investigator(s): Tamara Clegg
Funders: National Science Foundation
Research Areas: Data Science, Analytics, and Visualization Future of Work Health Informatics Human-Computer Interaction Information Justice, Human Rights, and Technology Ethics Social Networks, Online Communities, and Social Media Youth Experience, Learning, and Digital Practices
This project, DataGOAT, engages Black male collegiate athletes in data science by connecting their sports performance and health data to STEM learning. It aims to overcome racialized stereotypes, foster STEM identities, and create educational pathways through courses, internships, and data analysis tools, benefiting both participants and the broader educational community.
Principal Investigator(s): Tamara Clegg
Funders: National Science Foundation
Research Areas: Data Science, Analytics, and Visualization Future of Work Health Informatics Human-Computer Interaction Information Justice, Human Rights, and Technology Ethics Social Networks, Online Communities, and Social Media Youth Experience, Learning, and Digital Practices
This project, DataGOAT, engages Black male collegiate athletes in data science by connecting their sports performance and health data to STEM learning. It aims to overcome racialized stereotypes, foster STEM identities, and create educational pathways through courses, internships, and data analysis tools, benefiting both participants and the broader educational community.