Research Projects
Collaborative Research: ER2: The development of research ethics governance projects in computer science
Principal Investigator(s): Katie Shilton
Funders: National Science Foundation
Research Areas: Information Justice, Human Rights, and Technology Ethics
This project characterizes and evaluates historical, ongoing, and emerging ethics governance projects within computer science. By creating a recent history of computing governance during this active period of questioning, the project will appraise and evaluate current efforts, and recommend best practices for computing research governance.
Principal Investigator(s): Katie Shilton
Funders: National Science Foundation
Research Areas: Information Justice, Human Rights, and Technology Ethics
This project characterizes and evaluates historical, ongoing, and emerging ethics governance projects within computer science. By creating a recent history of computing governance during this active period of questioning, the project will appraise and evaluate current efforts, and recommend best practices for computing research governance.
Collaborative Research: Harmonizing Scratch Encore: Empowering Educators to Create Customized Culturally-Responsive Computing Materials
Principal Investigator(s): David Weintrop
Funders: National Science Foundation
Research Areas: Youth Experience, Learning, and Digital Practices
This project explores ways to support middle school computer science teachers in drawing on their students' cultural resources and prior knowledge to situate introductory computer science learning experiences.
Principal Investigator(s): David Weintrop
Funders: National Science Foundation
Research Areas: Youth Experience, Learning, and Digital Practices
This project explores ways to support middle school computer science teachers in drawing on their students' cultural resources and prior knowledge to situate introductory computer science learning experiences.
Collaborative Research: Impacts of Hard/Soft Skills on STEM Workforce Trajectories
Principal Investigator(s): Christopher Antoun
Funders: National Science Foundation
This project conducts a longitudinal study to examine how communication, leadership, and management skills influence PhD graduates’ career trajectories across academic and non-academic sectors. By linking individual, program, and employer data, researchers will provide evidence-based insights to strengthen doctoral training and workforce preparation.
Principal Investigator(s): Christopher Antoun
Funders: National Science Foundation
This project conducts a longitudinal study to examine how communication, leadership, and management skills influence PhD graduates’ career trajectories across academic and non-academic sectors. By linking individual, program, and employer data, researchers will provide evidence-based insights to strengthen doctoral training and workforce preparation.
Collaborative Research: SaTC: CORE: Medium: Supporting Privacy Negotiation Among Multiple Stakeholders in Smart Environments
Principal Investigator(s): Jessica Vitak
Funders: National Science Foundation
Research Areas: Data Privacy and Sociotechnical Cybersecurity
Internet-of-Things devices are increasingly used in shared spaces (e.g., homes, apartments, schools, hospitals, workplaces), and different stakeholders in these environments have unique privacy needs and expectations. This project investigates privacy negotiation behaviors in smart environments by designing, developing, and deploying an interactive system to collect people’s real-world privacy negotiation behaviors.
Principal Investigator(s): Jessica Vitak
Funders: National Science Foundation
Research Areas: Data Privacy and Sociotechnical Cybersecurity
Internet-of-Things devices are increasingly used in shared spaces (e.g., homes, apartments, schools, hospitals, workplaces), and different stakeholders in these environments have unique privacy needs and expectations. This project investigates privacy negotiation behaviors in smart environments by designing, developing, and deploying an interactive system to collect people’s real-world privacy negotiation behaviors.
Collaborative Research: Using Artificial Intelligence To Improve Administration of the Freedom of Information Act (FOIA)
Principal Investigator(s): Jason R. Baron Douglas W. Oard
Funders: Unfunded
Research Areas: Archival Science Machine Learning, AI, Computational Linguistics, and Information Retrieval
Memorandum of Understanding with MITRE Corporation to research the application of various forms of artificial intelligence (AI) including machine learning (ML) methods to aid in the redaction of documents corresponding to one or more FOIA exemptions.
Principal Investigator(s): Jason R. Baron Douglas W. Oard
Funders: Unfunded
Research Areas: Archival Science Machine Learning, AI, Computational Linguistics, and Information Retrieval
Memorandum of Understanding with MITRE Corporation to research the application of various forms of artificial intelligence (AI) including machine learning (ML) methods to aid in the redaction of documents corresponding to one or more FOIA exemptions.
Computational Thinking to Unlock the Japanese American WWII Camp Experience
Principal Investigator(s): Richard Marciano
Funders: Unfunded
Research Areas: Archival Science Machine Learning, AI, Computational Linguistics, and Information Retrieval
Exploring the legacy of WWII Japanese American Incarceration through computational archival science approaches.
Principal Investigator(s): Richard Marciano
Funders: Unfunded
Research Areas: Archival Science Machine Learning, AI, Computational Linguistics, and Information Retrieval
Exploring the legacy of WWII Japanese American Incarceration through computational archival science approaches.
Computational Treatments to re-member the Legacy of Slavery (CT-LoS)
Principal Investigator(s): Richard Marciano
Funders: Unfunded
Research Areas: Archival Science Data Science, Analytics, and Visualization Information Justice, Human Rights, and Technology Ethics
Using Computational Archival Science to unlock records related to the Legacy of Slavery and provide new point of interaction and analysis.
Principal Investigator(s): Richard Marciano
Funders: Unfunded
Research Areas: Archival Science Data Science, Analytics, and Visualization Information Justice, Human Rights, and Technology Ethics
Using Computational Archival Science to unlock records related to the Legacy of Slavery and provide new point of interaction and analysis.
Computer and Information Science and Engineering Graduate Fellowships (CSGrad4US) – Micah Morgan
Principal Investigator(s): Sheena Erete
Funders: National Science Foundation
Research Areas: Information Justice, Human Rights, and Technology Ethics Library and Information Science Youth Experience, Learning, and Digital Practices
The CSGrad4US Fellowship Program supports domestic bachelor’s degree holders returning to academia by providing mentoring and funding to pursue PhDs in computing. Through this cooperative agreement, the Computing Research Association will manage recruitment, applications, mentoring, and program evaluation to expand diversity in CISE fields.
Principal Investigator(s): Sheena Erete
Funders: National Science Foundation
Research Areas: Information Justice, Human Rights, and Technology Ethics Library and Information Science Youth Experience, Learning, and Digital Practices
The CSGrad4US Fellowship Program supports domestic bachelor’s degree holders returning to academia by providing mentoring and funding to pursue PhDs in computing. Through this cooperative agreement, the Computing Research Association will manage recruitment, applications, mentoring, and program evaluation to expand diversity in CISE fields.
Crowdsourced Data: Accuracy, Accessibility, Authority (CDAAA)
Principal Investigator(s): Victoria Van Hyning
Funders: Institute of Museum and Library Services
Research Areas: Accessibility and Inclusive Design Archival Science Digital Humanities Information Justice, Human Rights, and Technology Ethics Library and Information Science Social Networks, Online Communities, and Social Media
CDAAA explores the sociotechnical barriers libraries, archives, and museums face in integrating crowdsourced transcriptions to discovery systems.
Principal Investigator(s): Victoria Van Hyning
Funders: Institute of Museum and Library Services
Research Areas: Accessibility and Inclusive Design Archival Science Digital Humanities Information Justice, Human Rights, and Technology Ethics Library and Information Science Social Networks, Online Communities, and Social Media
CDAAA explores the sociotechnical barriers libraries, archives, and museums face in integrating crowdsourced transcriptions to discovery systems.
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.