To advance the research goals of the School of Data Science, the School is organizing Research Interest Groups around key areas. The groups will be comprised of a wide range of faculty who bring expertise to different aspects of these areas. The aim is to promote collaboration, which will lead to new, impactful insights.
Research Interest Group on Graph and Network Data
The Research Interest Group on Graph and Network Data within the School of Data Science focuses on the analysis and application of network science and graph neural networks. Network-structured data captures the interrelationships between entities and are a powerful tool for understanding complex systems across various domains, including social networks, transportation systems, brain networks, and biological networks. By studying network properties and dynamics, this group aims to develop advanced methodologies for analyzing, modeling, and visualizing complex data structures, facilitating interdisciplinary collaboration and contributing to the broader goals of data-driven research and innovation.
Contact: Alex Gates
Affiliated Faculty
Hudson Golino (Department of Psychology)
Jeff Saucerman (Department of Biomedical Engineering)
Nicholas Landry (Department of Biology, beginning fall 2024)
Research Interest Group on Brains in Data Science
The Research Interest Group on Brains in Data Science within the School of Data Science focuses on the application of modern data science methods to the study of neuroscience at any scale. Neuroscience here is broadly defined, from single cell recordings to human neuroimaging. This group aims to advance the field of neuroscience by bringing together data scientists and applied neuroscientists to facilitate collaboration. Please get in touch with our contact faculty if you are interested in joining (non-School of Data Science faculty and students welcome).
Contact: Teague Henry
Affiliated Faculty
Stefanie Sequeira (Department of Psychology)
Kevin Pelphrey (School of Medicine)