Research Projects
CAREER: Data-driven Models of Human Mobility and Resilience for Decision Making
Principal Investigator(s): Vanessa Frias-Martinez
Funder: National Science Foundation
Research Areas: Data Privacy and Sociotechnical Cybersecurity > Future of Work
Using cell-phone data to better understand the reactions and movement of people in violent or disaster events, specifically looking at droughts in Haiti, armed conflicts in Colombia, and floods in Bangladesh, with the aim of providing decision makers with data-driven models they can use to create preparedness and response plans.
Principal Investigator(s): Vanessa Frias-Martinez
Funder: National Science Foundation
Research Areas: Data Privacy and Sociotechnical Cybersecurity > Future of Work
Using cell-phone data to better understand the reactions and movement of people in violent or disaster events, specifically looking at droughts in Haiti, armed conflicts in Colombia, and floods in Bangladesh, with the aim of providing decision makers with data-driven models they can use to create preparedness and response plans.
Global Privacy Monitor (GMP): Learning from External Privacy Stakeholders
Principal Investigator(s): Frauke Kreuter
Research Areas: Data Privacy and Sociotechnical Cybersecurity
Principal Investigator(s): Frauke Kreuter
Research Areas: Data Privacy and Sociotechnical Cybersecurity
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.
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.
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
Funder: 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
Funder: 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.