Designed especially for neurobiologists, FluoRender is an interactive tool for multi-channel fluorescence microscopy data visualization and analysis.
Deep brain stimulation
BrainStimulator is a set of networks that are used in SCIRun to perform simulations of brain stimulation such as transcranial direct current stimulation (tDCS) and magnetic transcranial stimulation (TMS).
Developing software tools for science has always been a central vision of the SCI Institute.

Events on February 19, 2020

Ph.D. Thesis Defense

Carolina Nobre Presents:

Visualizing Multivariate Networks

February 19, 2020 at 9:00am for 1hr
Evans Conference Room, WEB 3780
Warnock Engineering Building, 3rd floor.


A multivariate network is one where the nodes and/or edges are associated with attributes. This type of network is widespread, with examples including social networks, physical networks such as power grids, networks modeling cellular processes in biology, and trees describing evolutionary relationships between species. The need for visualizing MVNs arises when the structure (the topology) of the network needs to be analyzed together with the node or edge attributes. This presents a challenge when visualizing topology and attributes in the same view, since choosing efficient encodings for one aspect often interferes with the ability to effectively visualize the other. Our work contributes to the space of multivariate network visualization by first organizing the design space of MVN visualization techniques into a typology and identifying the limits of existing approaches. Given this landscape of techniques, we make two technique contributions: (1) an applied design study with domain experts which explores visualizing attributed genealogies, and (2) a general MVNV visualization approach that addresses the challenge of simultaneously visualizing topology and attributes well. We also contribute an empirical study which provides experimental evidence on the performance of the two most commonly used MVNV techniques: node-link diagrams and adjacency matrices. Finally, we reflect on the evaluation component of the completed work, including challenges and potential alternative approaches in future work. This body of work will provide guidance for practitioners, visualization researchers, and domain experts using MVNs for real-world exploration.

Posted by: Nathan Galli