Research Projects
HCC: Small: The Incel Phenomenon: Assessing Radicalization and Deradicalization Online
Principal Investigator(s): Jennifer Golbeck
Funders: National Science Foundation
Principal Investigator(s): Jennifer Golbeck
Funders: National Science Foundation
III: Small: Bringing Transparency and Interpretability to Bias Mitigation Approaches in Place-based Mobility-centric Prediction Models for Decision
Principal Investigator(s): Vanessa Frias-Martinez
Funders: National Science Foundation
Research Areas: Data Science, Analytics, and Visualization Health Informatics Information Justice, Human Rights, and Technology Ethics Machine Learning, AI, Computational Linguistics, and Information Retrieval
The project focuses on improving the fairness of place-based mobility-centric (PBMC) prediction models, particularly in high-stakes scenarios like public health and safety. By addressing biases in COVID-19 mobility and case data, it aims to make predictions more accurate and equitable. The research introduces novel bias-mitigation and interpretability methods across three technical thrusts, promoting transparency in PBMC models.
Principal Investigator(s): Vanessa Frias-Martinez
Funders: National Science Foundation
Research Areas: Data Science, Analytics, and Visualization Health Informatics Information Justice, Human Rights, and Technology Ethics Machine Learning, AI, Computational Linguistics, and Information Retrieval
The project focuses on improving the fairness of place-based mobility-centric (PBMC) prediction models, particularly in high-stakes scenarios like public health and safety. By addressing biases in COVID-19 mobility and case data, it aims to make predictions more accurate and equitable. The research introduces novel bias-mitigation and interpretability methods across three technical thrusts, promoting transparency in PBMC models.
Inclusive ICT Rehabilitation Engineering Research Center (TRACE RERC)
Principal Investigator(s): J. Bern Jordan Amanda Lazar Hernisa Kacorri
Funders: Health and Human Services
Research Areas: Accessibility and Inclusive Design Data Privacy and Sociotechnical Cybersecurity Human-Computer Interaction
Principal Investigator(s): J. Bern Jordan Amanda Lazar Hernisa Kacorri
Funders: Health and Human Services
Research Areas: Accessibility and Inclusive Design Data Privacy and Sociotechnical Cybersecurity Human-Computer Interaction
Information Technology Access RERC
Principal Investigator(s): J. Bern Jordan Amanda Lazar Hernisa Kacorri
Funders: DHHS-Administration for Community Living Other Federal
Principal Investigator(s): J. Bern Jordan Amanda Lazar Hernisa Kacorri
Funders: DHHS-Administration for Community Living Other Federal
Information Technology Access RERC (Year 2)
Principal Investigator(s): J. Bern Jordan
Funders: Health and Human Services
Principal Investigator(s): J. Bern Jordan
Funders: Health and Human Services
Institute for Trustworthy AI in Law and Society (TRAILS)
Principal Investigator(s): Katie Shilton
Funders: National Science Foundation
Research Areas: Information Justice, Human Rights, and Technology Ethics Machine Learning, AI, Computational Linguistics, and Information Retrieval
The TRAILS (Trustworthy AI in Law and Society) Institute, a collaboration among several universities, aims to enhance trust in AI systems. It focuses on community participation, transparent design, and best practices. Four key research thrusts address social values, technical design, socio-technical perceptions, and governance. The institute seeks to include historically marginalized communities and promote informed AI adoption.
Principal Investigator(s): Katie Shilton
Funders: National Science Foundation
Research Areas: Information Justice, Human Rights, and Technology Ethics Machine Learning, AI, Computational Linguistics, and Information Retrieval
The TRAILS (Trustworthy AI in Law and Society) Institute, a collaboration among several universities, aims to enhance trust in AI systems. It focuses on community participation, transparent design, and best practices. Four key research thrusts address social values, technical design, socio-technical perceptions, and governance. The institute seeks to include historically marginalized communities and promote informed AI adoption.
Integration of Computer-Assisted Methods and Human Interactions to Understand Lesson Plan Quality and Teaching to Advance Middle-Grade Mathematics Instruction
Principal Investigator(s): Wei Ai
Funders: University of Washington Other Non-Federal
Research Areas: Human-Computer Interaction
Principal Investigator(s): Wei Ai
Funders: University of Washington Other Non-Federal
Research Areas: Human-Computer Interaction
Investigating the Information Practices of COVID Long-Haulers
Principal Investigator(s): Beth St. Jean Twanna Hodge Jane Behre J. Nicole Miller Miranda Downey
Funders: State of MD
Research Areas: Health Informatics Information Justice, Human Rights, and Technology Ethics Library and Information Science
This project investigates the information needs, practices, and experiences of people who have long COVID ("COVID long-haulers") in order to learn more about their COVID-related information needs, the ways in which they have gone about fulfilling these needs, and their information-related experiences. W
Principal Investigator(s): Beth St. Jean Twanna Hodge Jane Behre J. Nicole Miller Miranda Downey
Funders: State of MD
Research Areas: Health Informatics Information Justice, Human Rights, and Technology Ethics Library and Information Science
This project investigates the information needs, practices, and experiences of people who have long COVID ("COVID long-haulers") in order to learn more about their COVID-related information needs, the ways in which they have gone about fulfilling these needs, and their information-related experiences. W
Launching the TALENT Network to Promote the Training of Archival & Library Educators w. iNnovative Technologies
Principal Investigator(s): Richard Marciano
Funders: 8/1/2022 – 4/9/2025 Institute of Museum and Library Services
Research Areas: Archival Science Data Science, Analytics, and Visualization Library and Information Science
Creating a national community focused on developing digital expertise and leadership skills among archival and library educators.
Principal Investigator(s): Richard Marciano
Funders: 8/1/2022 – 4/9/2025 Institute of Museum and Library Services
Research Areas: Archival Science Data Science, Analytics, and Visualization Library and Information Science
Creating a national community focused on developing digital expertise and leadership skills among archival and library educators.
Libraries, Integration, and New Americans: Understanding immigrant acculturative stress
Principal Investigator(s): Ana Ndumu
Funders: 8/1/2021 – 7/31/2024 Institute of Museum and Library Services
Research Areas: Information Justice, Human Rights, and Technology Ethics Library and Information Science
This project aims to advance library and information science knowledge of immigrant well-being and increase capacity for libraries to serve as trusted spaces.
Principal Investigator(s): Ana Ndumu
Funders: 8/1/2021 – 7/31/2024 Institute of Museum and Library Services
Research Areas: Information Justice, Human Rights, and Technology Ethics Library and Information Science
This project aims to advance library and information science knowledge of immigrant well-being and increase capacity for libraries to serve as trusted spaces.
Machine Learning Strategies for FDR Presidential Library Collections (ML-FDR)
Principal Investigator(s): Richard Marciano
Funders: Unfunded
Research Areas: Archival Science Data Science, Analytics, and Visualization Machine Learning, AI, Computational Linguistics, and Information Retrieval
Demonstrate computational treatments of digital cultural assets using Artificial Intelligence (AI) and Machine Learning (ML) techniques that can help unlock hard-to-reach archival content related to WWII-era records housed at the FDR Presidential Library. This content is under-utilized by scholars examining American responses to the Holocaust.
Principal Investigator(s): Richard Marciano
Funders: Unfunded
Research Areas: Archival Science Data Science, Analytics, and Visualization Machine Learning, AI, Computational Linguistics, and Information Retrieval
Demonstrate computational treatments of digital cultural assets using Artificial Intelligence (AI) and Machine Learning (ML) techniques that can help unlock hard-to-reach archival content related to WWII-era records housed at the FDR Presidential Library. This content is under-utilized by scholars examining American responses to the Holocaust.
Maryland Institute for Digital Accessibility (MIDA)
Principal Investigator(s): Jonathan Lazar Paul T. Jaeger J. Bern Jordan Galina Madjaroff Reitz Katherine Izsak
Funders: State of MD
Research Areas: Accessibility and Inclusive Design Human-Computer Interaction Information Justice, Human Rights, and Technology Ethics
Principal Investigator(s): Jonathan Lazar Paul T. Jaeger J. Bern Jordan Galina Madjaroff Reitz Katherine Izsak
Funders: State of MD
Research Areas: Accessibility and Inclusive Design Human-Computer Interaction Information Justice, Human Rights, and Technology Ethics