Daniel Romero is studying how people on social media react during fast-changing situations such as natural disasters and political unrest, and how it affects information diffusion dynamics.
Nazanin Andalibi and colleagues will work with LGBTQ individuals who have experienced pregnancy loss with the ultimate goal of including marginalized individuals in technology design.
Thanks to a grant from the National Science Foundation, this project will conduct experiments with user communities to determine what motivates them to contribute metadata enhancements to archived data.
The study will carry out predictive analytics (using traditional statistical and machine learning tools) and geospatial analyses, to identify high risk individuals as well as those with identifiable kidney disease, and the geographic areas they live in, to better understand risk and progression factors for kidney disease.
With a grant from the Andrew W. Mellon Foundation, Paul Conway aims to create modularlized learning resources that support standards-based digitization of cultural heritage resources (still image, audio, video).
Creating credentialing infrastructure to enable collaboration, facilitate data reuse, make researchers' credentials more transparent, and make data accessible while respecting the privacy of data users.
UMSI's Ceren Budak aims to improve our understanding of how online movements are formed, how they evolve, how the participants coordinate, and how movements change their participants and the public.
UMSI's Erin Krupka is exploring how social norms and organizational identification affect employees, and developing interventions that can improve their behavior.
The study aims to a) develop a high fidelity acute kidney injury (AKI) risk prediction model for hospitalized Veterans; and b) develop an accompanying clinical decision support system (CDSS) to provide management recommendations for patients identified as being at higher risk for AKI.
