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. 

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)

Jeff Saucerman (Department of Biomedical Engineering)

Nicholas Landry (Department of Biology)

Brain Science & 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

Teague Henry

John Van Horn

Javier Rasero

Aiying Zhang

Heman Shakeri

Paul Perrin

Stefanie Sequeira (Department of Psychology)

Kevin Pelphrey (School of Medicine)

Gender and Technology

This RIG will sponsor a webinar series "Gender and Tech: Addressing Harms and Advancing Rights" to bring together leading scholars, advocates, practitioners, data scientists and tech experts to discuss the intersections of gender, technology, democracy and human rights. The goal is to critically examine how big data and digital technologies impact women, queer and gender-diverse individuals, while exploring pathways for more inclusive, rights-focused data and AI governance frameworks. The RIG will turn these discussions into a white paper with recommendations that will be published in the fall of 2025.

Contact: Jess Reia

Affiliated Faculty

Yasmin Curzi

Mar Hicks

Mona Sloane

Teaching & Learning Data Science

This RIG focuses on the scholarship of teaching and learning, specifically, documentign and evaluating UVA's approach to data science pedagogy.

Contact: Prince Afriyie

Affiliated Faculty

Mai Dahshan

Terence Johnson

Jonathan Kropko

Brian Wright
 

 

Environment & Data

This RIG focuses on the applications of data science to environmental problems, as well as the environmental impacts of data technologies (on water, energy consumption, climate change, etc.). It is co-sponsored with UVA's Environmental Institute.

Contact: tbd

Affiliated Faculty

under construction

Sports & Human Movement

This RIG focuses on sports analytics and the study of human movement. The group will host a Sports Summit in May 2025.

Contact: Natalie Kupperman

Affiliated Faculty

under construction

Data as Public Infrastructure

This RIG brings together faculty to explore the use of data science technologies by local and regional governments, nonprofit organizations and civil society groups.

Contact: Aaron Martin

Affiliated Faculty

Don Brown

Ryder Foley

Jon Kropko

Neal Magee

Jess Reia

Adam Tashman

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