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

Alex Gates

Paul Perrin

Aaron Abrams

Javier Rasero

Teague Henry

Jack Van Horn

Aidong Zhang

Sheng Li

Jundong Li

Aiying Zhang

Michael Porter

Heman Shakeri

Judy Fox

Hudson Golino (Department of Psychology)

Nick Laundry (Department of Biology, beginning fall 2024)