Research Projects
Piloting Lab Discourse Graphs for Sustainable Research Communication
Principal Investigator(s): Joel Chan
Funders: 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
Funders: 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.
Quantum Choreobotics: Democratizing Quantum Computing Through Interactive Dance/ Theater Performance, With On-Body Robots
Principal Investigator(s): Bill Kules
Funders: UMD Funded
Research Areas: Data Science, Analytics, and Visualization Digital Humanities Health Informatics Human-Computer Interaction Machine Learning, AI, Computational Linguistics, and Information Retrieval
UMD researchers Bill Kules and Huaishu Peng are exploring quantum choreobotics, an interactive dance-theater performance where audiences influence robot movements to engage with quantum technology concepts. The project uses art and performance to make complex scientific ideas accessible and thought-provoking for the public.
Principal Investigator(s): Bill Kules
Funders: UMD Funded
Research Areas: Data Science, Analytics, and Visualization Digital Humanities Health Informatics Human-Computer Interaction Machine Learning, AI, Computational Linguistics, and Information Retrieval
UMD researchers Bill Kules and Huaishu Peng are exploring quantum choreobotics, an interactive dance-theater performance where audiences influence robot movements to engage with quantum technology concepts. The project uses art and performance to make complex scientific ideas accessible and thought-provoking for the public.
Read, Watch, Play: Development of a Pedagogical Approach and Technical Infrastructure to Build Gamification, Game-Based Learning, and Other Hands-On Projects into Courses across Campus
Principal Investigator(s): Caro Williams-Pierce Andrew Fellows Katherine Izsak Pamela Duffy
Funders: State of MD
Research Areas: Youth Experience, Learning, and Digital Practices
Principal Investigator(s): Caro Williams-Pierce Andrew Fellows Katherine Izsak Pamela Duffy
Funders: State of MD
Research Areas: Youth Experience, Learning, and Digital Practices
Ready Now: Supporting Youth and Families During Crisis
Principal Investigator(s): Mega Subramaniam Nitzan Koren
Funders: 8/1/2023 - 4/9/2025 Institute of Museum and Library Services
Research Areas: Library and Information Science
This project aims to broaden and improve the efficacy of the publication: Library Staff as Public Servants: A Field Guide for Preparing to Support Communities in Crisis.
Principal Investigator(s): Mega Subramaniam Nitzan Koren
Funders: 8/1/2023 - 4/9/2025 Institute of Museum and Library Services
Research Areas: Library and Information Science
This project aims to broaden and improve the efficacy of the publication: Library Staff as Public Servants: A Field Guide for Preparing to Support Communities in Crisis.
Reducing the gender gap in AfD discussions: an evidence scoring approach
Principal Investigator(s): Giovanni Luca Ciampaglia
Funders: Wikimedia Foundation Other Non-Federal
Research Areas: Data Science, Analytics, and Visualization Social Networks, Online Communities, and Social Media
Principal Investigator(s): Giovanni Luca Ciampaglia
Funders: Wikimedia Foundation Other Non-Federal
Research Areas: Data Science, Analytics, and Visualization Social Networks, Online Communities, and Social Media
Revolutionizing Space-Based ISR through Decentralized Systems & In-Orbit ML Computing for Near-Real-Time Intelligence
Principal Investigator(s): Sergii Skakun
Funders: Little Place Labs Other Non-Federal
Principal Investigator(s): Sergii Skakun
Funders: Little Place Labs Other Non-Federal
SaTC: CORE: Medium: Collaborative: BaitBuster 2.0: Keeping Users Away From Clickbait
Principal Investigator(s): Naeemul Hassan
Funders: National Science Foundation
Research Areas: Machine Learning, AI, Computational Linguistics, and Information Retrieval Data Privacy and Sociotechnical Cybersecurity Data Science, Analytics, and Visualization Social Networks, Online Communities, and Social Media
Developing novel techniques - through the application of state-of-the-art machine learning - to detect various forms of clickbait, especially video-based clickbait, and study user behavior on social media to design effective warning systems.
Principal Investigator(s): Naeemul Hassan
Funders: National Science Foundation
Research Areas: Machine Learning, AI, Computational Linguistics, and Information Retrieval Data Privacy and Sociotechnical Cybersecurity Data Science, Analytics, and Visualization Social Networks, Online Communities, and Social Media
Developing novel techniques - through the application of state-of-the-art machine learning - to detect various forms of clickbait, especially video-based clickbait, and study user behavior on social media to design effective warning systems.
SaTC: CORE: Medium: Learning Code(s): Community-Centered Design of Automated Content Moderation
Principal Investigator(s): Katie Shilton
Funders: National Science Foundation
Research Areas: Machine Learning, AI, Computational Linguistics, and Information Retrieval Social Networks, Online Communities, and Social Media
This research project aims to improve online community moderation by using machine learning and natural language processing. It focuses on learning from existing community decisions, supporting moderators, and creating adaptable tools. The goal is healthier online spaces and better working conditions for moderators.
Principal Investigator(s): Katie Shilton
Funders: National Science Foundation
Research Areas: Machine Learning, AI, Computational Linguistics, and Information Retrieval Social Networks, Online Communities, and Social Media
This research project aims to improve online community moderation by using machine learning and natural language processing. It focuses on learning from existing community decisions, supporting moderators, and creating adaptable tools. The goal is healthier online spaces and better working conditions for moderators.
SCC-IRG Track 1: Inclusive Public Transit Toolkit to Assess Quality of Service Across Socioeconomic Status in Baltimore City
Principal Investigator(s): Vanessa Frias-Martinez
Funders: National Science Foundation
Research Areas: Data Privacy and Sociotechnical Cybersecurity Data Science, Analytics, and Visualization Smart Cities and Connected Communities
Improving public transit for lower-income individuals - who often endure complex, lengthy trips - by providing a methods, guidelines, and a toolkit to identify and characterize the challenges typical of such complex trips.
Principal Investigator(s): Vanessa Frias-Martinez
Funders: National Science Foundation
Research Areas: Data Privacy and Sociotechnical Cybersecurity Data Science, Analytics, and Visualization Smart Cities and Connected Communities
Improving public transit for lower-income individuals - who often endure complex, lengthy trips - by providing a methods, guidelines, and a toolkit to identify and characterize the challenges typical of such complex trips.
Semantic Foundations and Formal Methods for Evolutionary System-of-Systems
Principal Investigator(s): Jennifer Golbeck
Funders: DoD-Defense
Semantic Foundations and Formal Methods for Evolutionary System-of-Systems is a three-year U.S. Army contract led by PI Mark Austin.
Principal Investigator(s): Jennifer Golbeck
Funders: DoD-Defense
Semantic Foundations and Formal Methods for Evolutionary System-of-Systems is a three-year U.S. Army contract led by PI Mark Austin.
TechBridge: Fostering Digital Literacy and Intergenerational Connection in Montgomery County
Principal Investigator(s): Galina Madjaroff Reitz
Funders: State of MD
Research Areas: Accessibility and Inclusive Design Human-Computer Interaction Youth Experience, Learning, and Digital Practices
Principal Investigator(s): Galina Madjaroff Reitz
Funders: State of MD
Research Areas: Accessibility and Inclusive Design Human-Computer Interaction Youth Experience, Learning, and Digital Practices
Testbed for the Redlining Archives of California’s Exclusionary Spaces (T-RACES)
Principal Investigator(s): Richard Marciano
Funders: Unfunded
Research Areas: Archival Science Data Science, Analytics, and Visualization Library and Information Science Machine Learning, AI, Computational Linguistics, and Information Retrieval
Making publicly accessible online documents relating to the practice of “redlining” neighborhoods in the 1930s and 1940s in eight California cities. “Redlining” refers to the practice of flagging minority neighborhoods as undesirable for home loans. The project creates a searchable database and interactive map interface.
Principal Investigator(s): Richard Marciano
Funders: Unfunded
Research Areas: Archival Science Data Science, Analytics, and Visualization Library and Information Science Machine Learning, AI, Computational Linguistics, and Information Retrieval
Making publicly accessible online documents relating to the practice of “redlining” neighborhoods in the 1930s and 1940s in eight California cities. “Redlining” refers to the practice of flagging minority neighborhoods as undesirable for home loans. The project creates a searchable database and interactive map interface.