Research Projects

Accelerating Cross-Disciplinary Innovation with Computational Analogy
Principal Investigator(s): Joel Chan
Funder: US Office of Naval Research
Research Areas: Computational Linguistics, Machine Learning, and Information Retrieval
Investigating how to develop interactive search engines that enable scientists and inventors to discover and adapt ideas across disciplinary boundaries.
Capturing Computational Thinking Literacy Development in Public Libraries
Principal Investigator(s): Mega Subramaniam
Funder: Institute of Museum and Library Services
Research Areas: Computational Linguistics, Machine Learning, and Information Retrieval > Library and Information Science
Identifying the learning outcomes that can be achieved through CT programs for youth offered through libraries and to develop a bank of assessment tools that can be used by public library staff to document and measure CT literacy development in youth as a result of participating in library CT programs.
IARPA BETTER: Multilingual Fine-grained Decompositional Analysis
Principal Investigator(s):
Funder: USODNI Intelligence Advanced Research Projects Activity
Research Areas: Computational Linguistics, Machine Learning, and Information Retrieval
Developing enhanced methods for personalized, multilingual semantic extraction and retrieval from text, in support of IARPA's goal of providing users with a system that quickly and accurately extracts complex semantic information, targeted for a specific user, from text.
III: Small: DataWorld: Externalizing Hidden Data Flows for Anywhere Analytics
Principal Investigator(s): Niklas Elmqvist
Funder: National Science Foundation
Research Areas: Computational Linguistics, Machine Learning, and Information Retrieval > Data Science, Analytics, and Visualization > Information Justice, Human Rights, and Technology Ethics > Library and Information Science
Building an augmented-reality DataWorld using hidden troves of data (from social media, the census, public databases, and more) to help professionals, policymakers, and citizens in there every day life---from house hunting by walking through the neighborhood and getting pop-up facts about the area to getting event and safety updates as you walk through a college campus.
Piloting an Online National Collaborative Network for Integrating Computational Thinking into Library and Archival Education and Practice
Principal Investigator(s): Richard Marciano
Funder: Institute of Museum and Library Services
Research Areas: Computational Archival Science > Computational Linguistics, Machine Learning, and Information Retrieval > Data Science, Analytics, and Visualization > Information Justice, Human Rights, and Technology Ethics > Library and Information Science
Piloting an online national collaborative network of educators and practitioners to enable the sharing and dissemination of computational case studies and lesson plans through an open source, cloud-based interactive platform based on Jupyter Notebooks.
SaTC: CORE: Medium: Collaborative: BaitBuster 2.0: Keeping Users Away From Clickbait
Principal Investigator(s): Naeemul Hassan
Funder: National Science Foundation
Research Areas: Computational Linguistics, Machine Learning, and Information Retrieval > Data Privacy and Sociotechnical Cybersecurity > Data Science, Analytics, and Visualization > Social Networks and Online Communities
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: EDU: Collaborative: Connecting Contexts: Building Foundational Digital Privacy and Security Skills for Elementary School Children, Teachers, and Parents
Principal Investigator(s): Jessica Vitak Tamara Clegg
Funder: National Science Foundation
Research Areas: Accessibility and Inclusive Design > Computational Linguistics, Machine Learning, and Information Retrieval > Data Science, Analytics, and Visualization > Human-Computer Interaction
Promoting elementary school children's privacy/cybersecurity learning across the two contexts where they spend most of their time, home and school, through the creation of curriculum and related educational materials tailored to grade level.

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