Research Projects
Filtered by: Future of Work
Developing and Investigating Data Science Interventions Connected to University Athletics to Address Systemic Racism in Undergraduate STEM Education (better known as DataGOAT)
Principal Investigator(s): Tamara Clegg
Funders: National Science Foundation
Research Areas: Data Science, Analytics, and Visualization Future of Work Health Informatics Human-Computer Interaction Information Justice, Human Rights, and Technology Ethics Social Networks, Online Communities, and Social Media Youth Experience, Learning, and Digital Practices
This project, DataGOAT, engages Black male collegiate athletes in data science by connecting their sports performance and health data to STEM learning. It aims to overcome racialized stereotypes, foster STEM identities, and create educational pathways through courses, internships, and data analysis tools, benefiting both participants and the broader educational community.
Principal Investigator(s): Tamara Clegg
Funders: National Science Foundation
Research Areas: Data Science, Analytics, and Visualization Future of Work Health Informatics Human-Computer Interaction Information Justice, Human Rights, and Technology Ethics Social Networks, Online Communities, and Social Media Youth Experience, Learning, and Digital Practices
This project, DataGOAT, engages Black male collegiate athletes in data science by connecting their sports performance and health data to STEM learning. It aims to overcome racialized stereotypes, foster STEM identities, and create educational pathways through courses, internships, and data analysis tools, benefiting both participants and the broader educational community.
E-VERIFY: Task Order 002: Mission Analytics Technology and Research for Innovative eXploitation (MATRIX)
Principal Investigator(s): Cody Buntain
Funders: Parallax Advanced Research Other Federal
Research Areas: Data Science, Analytics, and Visualization Future of Work Machine Learning, AI, Computational Linguistics, and Information Retrieval
This project focuses on developing mathematical and computational methods to advance machine learning and artificial intelligence, with applications that support U.S. Air Force, U.S. Space Force, and Department of Defense personnel.
Principal Investigator(s): Cody Buntain
Funders: Parallax Advanced Research Other Federal
Research Areas: Data Science, Analytics, and Visualization Future of Work Machine Learning, AI, Computational Linguistics, and Information Retrieval
This project focuses on developing mathematical and computational methods to advance machine learning and artificial intelligence, with applications that support U.S. Air Force, U.S. Space Force, and Department of Defense personnel.
Enhancing Performance and Communication for Distributed Teams During Lunar Spacewalks
Principal Investigator(s): Susannah Paletz
Funders: NASA - Johnson Space Center Other Federal
Research Areas: Future of Work Human-Computer Interaction Machine Learning, AI, Computational Linguistics, and Information Retrieval
Principal Investigator(s): Susannah Paletz
Funders: NASA - Johnson Space Center Other Federal
Research Areas: Future of Work Human-Computer Interaction Machine Learning, AI, Computational Linguistics, and Information Retrieval
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: Data Science, Analytics, and Visualization Future of Work Human-Computer Interaction Machine Learning, AI, Computational Linguistics, and Information Retrieval Youth Experience, Learning, and Digital Practices
This NSF-funded project uses machine learning, human coding, and teacher input to evaluate the quality of middle-grades mathematics lesson plans. By combining computational analysis with educator perspectives, it aims to improve how instructional materials are assessed and used in classrooms.
Principal Investigator(s): Wei Ai
Funders: University of Washington Other Non-Federal
Research Areas: Data Science, Analytics, and Visualization Future of Work Human-Computer Interaction Machine Learning, AI, Computational Linguistics, and Information Retrieval Youth Experience, Learning, and Digital Practices
This NSF-funded project uses machine learning, human coding, and teacher input to evaluate the quality of middle-grades mathematics lesson plans. By combining computational analysis with educator perspectives, it aims to improve how instructional materials are assessed and used in classrooms.
NSF Convergence Accelerator Track J: NourishNet – A Food Recovery Toolbox
Principal Investigator(s): Vanessa Frias-Martinez
Funders: National Science Foundation
Research Areas: Data Science, Analytics, and Visualization Future of Work Human-Computer Interaction Information Justice, Human Rights, and Technology Ethics Smart Cities and Connected Communities
NourishNet is developing tools to fight food insecurity and waste, including FoodLoops, a platform for surplus food distribution, and Quantum Nose, a sensor that detects early food spoilage. By combining real-time data, consumer education, and stakeholder collaboration, the project strengthens food system resiliency and promotes equitable access to healthy food.
Principal Investigator(s): Vanessa Frias-Martinez
Funders: National Science Foundation
Research Areas: Data Science, Analytics, and Visualization Future of Work Human-Computer Interaction Information Justice, Human Rights, and Technology Ethics Smart Cities and Connected Communities
NourishNet is developing tools to fight food insecurity and waste, including FoodLoops, a platform for surplus food distribution, and Quantum Nose, a sensor that detects early food spoilage. By combining real-time data, consumer education, and stakeholder collaboration, the project strengthens food system resiliency and promotes equitable access to healthy food.