Research Projects
2023 Including Disability Global Summit
Principal Investigator(s): Paul T. Jaeger
Research Areas: Accessibility and Inclusive Design
Principal Investigator(s): Paul T. Jaeger
Research Areas: Accessibility and Inclusive Design
A Leaderboard and Competition for Human–Computer Adversarial QA
Principal Investigator(s): Jordan Boyd-Graber
Funder: Meta Platforms fka Facebook Other
Principal Investigator(s): Jordan Boyd-Graber
Funder: Meta Platforms fka Facebook Other
Accelerating Cross-Disciplinary Innovation with Computational Analogy
Principal Investigator(s): Joel Chan
Funder: US Office of Naval Research
Research Areas: Machine Learning, AI, Computational Linguistics, and Information Retrieval
Investigating how to develop interactive search engines that enable scientists and inventors to discover and adapt ideas across disciplinary boundaries.
Principal Investigator(s): Joel Chan
Funder: US Office of Naval Research
Research Areas: Machine Learning, AI, Computational Linguistics, and Information Retrieval
Investigating how to develop interactive search engines that enable scientists and inventors to discover and adapt ideas across disciplinary boundaries.
Accessible Visualization for Blind Users
Principal Investigator(s):
Research Areas: Accessibility and Inclusive Design
This project aims to enhance accessibility to large-scale data analysis for blind and low-vision individuals, bridging the gap in current tools and technologies. It focuses on creating cost-effective, user-friendly data representations based on sound, touch, and physical computing. The research involves understanding user needs and designing practical accessible data applications in collaboration with the blind community.
Principal Investigator(s):
Research Areas: Accessibility and Inclusive Design
This project aims to enhance accessibility to large-scale data analysis for blind and low-vision individuals, bridging the gap in current tools and technologies. It focuses on creating cost-effective, user-friendly data representations based on sound, touch, and physical computing. The research involves understanding user needs and designing practical accessible data applications in collaboration with the blind community.
Achieving Optimal Motor Function in Stroke Survivors via a Human-Centered Approach to Design an mHealth Platform
Principal Investigator(s): Eun Kyoung Choe
Funder: National Institutes of Health Other
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
Funder: National Institutes of Health Other
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
Additive Manufacturing Digital Curation and Data Management
Principal Investigator(s): Richard Marciano
Funder: US Army Research Office: Army Research Lab (ARL) Other
Research Areas: Archival Science > Data Science, Analytics, and Visualization
Exploring digital curation, data management, data mining, and the development of a digital asset management system for Additive Manufacturing
Principal Investigator(s): Richard Marciano
Funder: US Army Research Office: Army Research Lab (ARL) Other
Research Areas: Archival Science > Data Science, Analytics, and Visualization
Exploring digital curation, data management, data mining, and the development of a digital asset management system for Additive Manufacturing
Advancing Personal Informatics through Semi-Automated Tracking
Principal Investigator(s): Eun Kyoung Choe
Funder: National Science Foundation
Research Areas: Accessibility and Inclusive Design > Health Informatics > Human-Computer Interaction
Challenging the notion that fully automated health tracking tech is better for users, particularly older adults and surgical patients, since minimal personal tracking engagement is needed. This project examines semi-automated tracking, testing the hypothesis that some self-monitoring results in greater awareness of one's own health and data and better health/behavior outcomes.
Principal Investigator(s): Eun Kyoung Choe
Funder: National Science Foundation
Research Areas: Accessibility and Inclusive Design > Health Informatics > Human-Computer Interaction
Challenging the notion that fully automated health tracking tech is better for users, particularly older adults and surgical patients, since minimal personal tracking engagement is needed. This project examines semi-automated tracking, testing the hypothesis that some self-monitoring results in greater awareness of one's own health and data and better health/behavior outcomes.
An Assessment of Pretrial Risk across Maryland Jurisdictions using Client Legal Utility Enging (CLUE) Data
Principal Investigator(s): Zubin Jelveh
Funder: STMD-Governor's Office of Crime Control & Prevention Other
Research Areas: Archival Science > Data Science, Analytics, and Visualization > Information Justice, Human Rights, and Technology Ethics
With funding from the Maryland Governor's Office of Crime Control and Prevention, the project aims to understand why pretrial detention decisions are made and whether they align with the risk posed by defendants. By analyzing a large dataset of criminal cases, the team will investigate the predictability of pretrial risk and the court's decision-making. The research will provide insights to improve policy and practice, reducing unnecessary detention while ensuring public safety.
Principal Investigator(s): Zubin Jelveh
Funder: STMD-Governor's Office of Crime Control & Prevention Other
Research Areas: Archival Science > Data Science, Analytics, and Visualization > Information Justice, Human Rights, and Technology Ethics
With funding from the Maryland Governor's Office of Crime Control and Prevention, the project aims to understand why pretrial detention decisions are made and whether they align with the risk posed by defendants. By analyzing a large dataset of criminal cases, the team will investigate the predictability of pretrial risk and the court's decision-making. The research will provide insights to improve policy and practice, reducing unnecessary detention while ensuring public safety.
Building a sustainable future for anthropology’s archives: Researching primary source data lifecycles, infrastructures, and reuse
Principal Investigator(s): Diana E. Marsh Katrina Fenlon
Funder: National Science Foundation
This project aims to improve the preservation and accessibility of valuable, unpublished anthropological data, including field notebooks, recordings, and photographs. It investigates barriers to data reusability and seeks sustainable ways to adapt linked data infrastructures. The research involves focus group discussions, open access platforms, training modules, and a virtual symposium to enhance the sharing of primary source cultural research data and support interdisciplinary collaboration in anthropology.
Principal Investigator(s): Diana E. Marsh Katrina Fenlon
Funder: National Science Foundation
This project aims to improve the preservation and accessibility of valuable, unpublished anthropological data, including field notebooks, recordings, and photographs. It investigates barriers to data reusability and seeks sustainable ways to adapt linked data infrastructures. The research involves focus group discussions, open access platforms, training modules, and a virtual symposium to enhance the sharing of primary source cultural research data and support interdisciplinary collaboration in anthropology.
Capturing Computational Thinking Literacy Development in Public Libraries
Principal Investigator(s): Mega Subramaniam
Funder: Institute of Museum and Library Services
Research Areas: Machine Learning, AI, Computational Linguistics, and Information Retrieval > Library and Information Science
Identifying the learning outcomes that can be achieved through CT programs for youth offered through libraries and to develop a bank of assessment tools that can be used by public library staff to document and measure CT literacy development in youth as a result of participating in library CT programs.
Principal Investigator(s): Mega Subramaniam
Funder: Institute of Museum and Library Services
Research Areas: Machine Learning, AI, Computational Linguistics, and Information Retrieval > Library and Information Science
Identifying the learning outcomes that can be achieved through CT programs for youth offered through libraries and to develop a bank of assessment tools that can be used by public library staff to document and measure CT literacy development in youth as a result of participating in library CT programs.
CAREER: Advancing Remote Collaboration: Inclusive Design for People with Dementia
Principal Investigator(s): Amanda Lazar
Funder: 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
Funder: 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: Data-driven Models of Human Mobility and Resilience for Decision Making
Principal Investigator(s): Vanessa Frias-Martinez
Funder: National Science Foundation
Research Areas: Data Privacy and Sociotechnical Cybersecurity > Future of Work
Using cell-phone data to better understand the reactions and movement of people in violent or disaster events, specifically looking at droughts in Haiti, armed conflicts in Colombia, and floods in Bangladesh, with the aim of providing decision makers with data-driven models they can use to create preparedness and response plans.
Principal Investigator(s): Vanessa Frias-Martinez
Funder: National Science Foundation
Research Areas: Data Privacy and Sociotechnical Cybersecurity > Future of Work
Using cell-phone data to better understand the reactions and movement of people in violent or disaster events, specifically looking at droughts in Haiti, armed conflicts in Colombia, and floods in Bangladesh, with the aim of providing decision makers with data-driven models they can use to create preparedness and response plans.