Inactive Research Projects
CAREER: Ubilytics: Harnessing Existing Device Ecosystems for Anywhere Sensemaking
Principal Investigator(s):
Funder: National Science Foundation
Research Areas: Data Science, Analytics, and Visualization > Human-Computer Interaction > Smart Cities and Connected Communities
Proposing a comprehensive new approach called ubiquitous analytics (ubilytics) for harnessing ever-present digital devices into unified environments for anywhere analysis and sensemaking of data. Looking at applications for scientific discovery, classroom learning, and police investigation.
Principal Investigator(s):
Funder: National Science Foundation
Research Areas: Data Science, Analytics, and Visualization > Human-Computer Interaction > Smart Cities and Connected Communities
Proposing a comprehensive new approach called ubiquitous analytics (ubilytics) for harnessing ever-present digital devices into unified environments for anywhere analysis and sensemaking of data. Looking at applications for scientific discovery, classroom learning, and police investigation.
CCE STEM: Finding Practices that Cultivate Ethical Computing in Mobile and Wearable Application Research & Development
Principal Investigator(s): Katie Shilton
Funder: National Science Foundation
Research Areas: Data Privacy and Sociotechnical Cybersecurity > Data Science, Analytics, and Visualization > Information Justice, Human Rights, and Technology Ethics
Looking at mobile and wearable app development to discover factors that encourage discussion and action on ethical challenges amongst developers. Findings will be incorporated into curriculum for students in mobile app courses, and the impact on ethics education will be evaluated.
Principal Investigator(s): Katie Shilton
Funder: National Science Foundation
Research Areas: Data Privacy and Sociotechnical Cybersecurity > Data Science, Analytics, and Visualization > Information Justice, Human Rights, and Technology Ethics
Looking at mobile and wearable app development to discover factors that encourage discussion and action on ethical challenges amongst developers. Findings will be incorporated into curriculum for students in mobile app courses, and the impact on ethics education will be evaluated.
CCE STEM: Standard: Collaborative: The Development of Ethical Cultures in Computer Security Research
Principal Investigator(s): Katie Shilton
Funder: National Science Foundation
Research Areas: Data Privacy and Sociotechnical Cybersecurity > Information Justice, Human Rights, and Technology Ethics
Examining how computer security researchers navigate ethical dilemmas when using big data and shared network resources to expose vulnerabilities - from ethical self-regulation to the sharing of ethics expectations in research communities.
Principal Investigator(s): Katie Shilton
Funder: National Science Foundation
Research Areas: Data Privacy and Sociotechnical Cybersecurity > Information Justice, Human Rights, and Technology Ethics
Examining how computer security researchers navigate ethical dilemmas when using big data and shared network resources to expose vulnerabilities - from ethical self-regulation to the sharing of ethics expectations in research communities.
Center For Excellence in Human Language Technology
Principal Investigator(s): Douglas W. Oard
Funder: Johns Hopkins University Other Non-Federal
Research Areas: Machine Learning, AI, Computational Linguistics, and Information Retrieval > Human-Computer Interaction
Principal Investigator(s): Douglas W. Oard
Funder: Johns Hopkins University Other Non-Federal
Research Areas: Machine Learning, AI, Computational Linguistics, and Information Retrieval > Human-Computer Interaction
Center for Excellence in Human Language Technology (COE HLT) TTO8.16-21
Principal Investigator(s): Douglas W. Oard
Funder: Johns Hopkins University Other Non-Federal
Research Areas: Machine Learning, AI, Computational Linguistics, and Information Retrieval > Data Science, Analytics, and Visualization
Exploring highly innovative technologies to automatically analyze a wide range of speech, text, and document data in multiple languages.
Principal Investigator(s): Douglas W. Oard
Funder: Johns Hopkins University Other Non-Federal
Research Areas: Machine Learning, AI, Computational Linguistics, and Information Retrieval > Data Science, Analytics, and Visualization
Exploring highly innovative technologies to automatically analyze a wide range of speech, text, and document data in multiple languages.
CHS: Small: Collaborative Research: Making Information Deserts Visible: Computational Models, Disparities in Civic Technology Use, and Urban Decision Making
Principal Investigator(s):
Research Areas: Information Justice, Human Rights, and Technology Ethics > Smart Cities and Connected Communities
Enhancing understanding of how civic technologies are used and how information inequalities manifest in a city by examining Boston's 311 system for reporting non-emergency issues to the city government and then using computational and qualitative approaches to identify, categorize, and understand the kinds of information disparities that are becoming institutionalized.
Principal Investigator(s):
Research Areas: Information Justice, Human Rights, and Technology Ethics > Smart Cities and Connected Communities
Enhancing understanding of how civic technologies are used and how information inequalities manifest in a city by examining Boston's 311 system for reporting non-emergency issues to the city government and then using computational and qualitative approaches to identify, categorize, and understand the kinds of information disparities that are becoming institutionalized.
CHS: Small: Collaborative Research: Toolkits for Aging in Place for Older Retirees (TAIPOR)
Principal Investigator(s): Amanda Lazar
Funder: National Science Foundation
Research Areas: Health Informatics > Human-Computer Interaction
Principal Investigator(s): Amanda Lazar
Funder: National Science Foundation
Research Areas: Health Informatics > Human-Computer Interaction
CHS: Small: Innovation Through Analogical Search
Principal Investigator(s): Joel Chan
Funder: Carnegie Mellon University Other Non-Federal
Research Areas: Machine Learning, AI, Computational Linguistics, and Information Retrieval > Data Science, Analytics, and Visualization
Building computational tools enabling users to connect problems in one field with solutions from another field, i.e. facilitate searching for analogies drawn from one domain to help with innovative thinking and reasoning in another domain.
Principal Investigator(s): Joel Chan
Funder: Carnegie Mellon University Other Non-Federal
Research Areas: Machine Learning, AI, Computational Linguistics, and Information Retrieval > Data Science, Analytics, and Visualization
Building computational tools enabling users to connect problems in one field with solutions from another field, i.e. facilitate searching for analogies drawn from one domain to help with innovative thinking and reasoning in another domain.
CHS: Small: Teachable Object Recognizers for the Blind
Principal Investigator(s): Hernisa Kacorri
Funder: National Science Foundation
Research Areas: Accessibility and Inclusive Design > Human-Computer Interaction > Machine Learning, AI, Computational Linguistics, and Information Retrieval
The research aims to develop a teachable object recognizer (TOR) app for blind users, enabling them to train machine learning models with personalized data through their smartphone cameras. This "teachability" approach addresses data scarcity in assistive technology. The study will explore effective user training, measure system efficacy, and evaluate accessible interactions through various research methods, aiming to improve the robustness of assistive tech.
Principal Investigator(s): Hernisa Kacorri
Funder: National Science Foundation
Research Areas: Accessibility and Inclusive Design > Human-Computer Interaction > Machine Learning, AI, Computational Linguistics, and Information Retrieval
The research aims to develop a teachable object recognizer (TOR) app for blind users, enabling them to train machine learning models with personalized data through their smartphone cameras. This "teachability" approach addresses data scarcity in assistive technology. The study will explore effective user training, measure system efficacy, and evaluate accessible interactions through various research methods, aiming to improve the robustness of assistive tech.
Civil Rights in the National Capital Region: A research-driven exhibition in collaboration with the National Park Service
Principal Investigator(s): Diana E. Marsh
Research Areas: Machine Learning, AI, Computational Linguistics, and Information Retrieval > Data Science, Analytics, and Visualization > Library and Information Science > Youth Experience, Learning, and Digital Practices
Students are working with Dr. Marsh and NPS curators throughout the 2020-2021 academic year to research and produce an online exhibit highlighting NPS sites and materials in the National Capital Region related to the history of civil rights. Drawing on the heritage sites and collections holdings of the NPS in the National Capital Region, the interns are assisting curators in all aspects of research and content development, with a broader goal to increase public awareness of the NPS sites and collections in the National Capital Region.
Principal Investigator(s): Diana E. Marsh
Research Areas: Machine Learning, AI, Computational Linguistics, and Information Retrieval > Data Science, Analytics, and Visualization > Library and Information Science > Youth Experience, Learning, and Digital Practices
Students are working with Dr. Marsh and NPS curators throughout the 2020-2021 academic year to research and produce an online exhibit highlighting NPS sites and materials in the National Capital Region related to the history of civil rights. Drawing on the heritage sites and collections holdings of the NPS in the National Capital Region, the interns are assisting curators in all aspects of research and content development, with a broader goal to increase public awareness of the NPS sites and collections in the National Capital Region.
Collaboration in the Future of Work: Developing Playable Case Studies to Improve STEM Career Pathways
Principal Investigator(s): beth bonsignore
Funder: National Science Foundation
Research Areas: Data Science, Analytics, and Visualization > Future of Work > Youth Experience, Learning, and Digital Practices
Developing role playing computer games for the classroom to encourage STEM learning. Students can collaborate with each other and fictional characters in an authentic scenario using a multimedia interface supported by chatbots, videoconferencing, and interactive STEM tools.
Principal Investigator(s): beth bonsignore
Funder: National Science Foundation
Research Areas: Data Science, Analytics, and Visualization > Future of Work > Youth Experience, Learning, and Digital Practices
Developing role playing computer games for the classroom to encourage STEM learning. Students can collaborate with each other and fictional characters in an authentic scenario using a multimedia interface supported by chatbots, videoconferencing, and interactive STEM tools.
Collaboration Network for Excellent Education and Research in Dependable and Secure Distributed Systems (CREDENCE)
Principal Investigator(s): Keith Marzullo
Funder: University System of Maryland Foundation Inc. Other Non-Federal
Research Areas: Smart Cities and Connected Communities
Building a collaborative network of leading computer science departments and laboratories in Brazil, Canada and the US to advance the design and validation of security/reliability-critical distributed systems, such as smart homes and cities, cloud computing, smart energy and cryptocurrency systems.
Principal Investigator(s): Keith Marzullo
Funder: University System of Maryland Foundation Inc. Other Non-Federal
Research Areas: Smart Cities and Connected Communities
Building a collaborative network of leading computer science departments and laboratories in Brazil, Canada and the US to advance the design and validation of security/reliability-critical distributed systems, such as smart homes and cities, cloud computing, smart energy and cryptocurrency systems.