About Me

I am an Assistant Professor at the University of Florida in the Department of Computer & Information Science & Engineering (CISE). I lead the Indie (Interactive Data and Immersive Environments) research lab. The Indie Lab conducts research in areas including human-computer interaction (HCI), human-centered computing (HCC), information visualization, virtual reality, 3D interaction, visual analytics, and trust in intelligent systems.

Previously, I was an assistant professor at Texas A&M University with the Department of Visualization and the Department of Computer Science & Engineering. Before that, I worked as a visual analytics research scientist at Oak Ridge National Laboratory as part of the Situation Awareness and Visual Analytics research team. I received my Ph.D in Computer Science from Virginia Tech, where I worked with Dr. Doug Bowman on immersive virtual reality research in the 3D Interaction group.

My CV is available for more information about me.



Eric D. Ragan, PhD
Assistant Professor
University of Florida
eragan@ufl.edu

Indie Research

The Indie (Interactive Data and Immersive Environments) Lab is a research lab within the Department of Computer & Information Science & Engineering (CISE) at the University of Florida. The Indie Lab engages in human-centered research of interactive visualizations. Our research focuses on the design and evaluation of applications and techniques that support effective interaction and understanding of data, information, and virtual environments. Research areas include information visualization, virtual reality, 3D interaction, visual analytics, and explainable AI. The group includes undergraduate and graduate students from multiple departments, and we actively collaborate with faculty across the university.

Upcoming Events

TREX 2020: Workshop on TRust and EXperience in Visual Analytics at IEEE VIS 2020!

This workshop invites contributions that provide a user-centered perspective on how human-machine trust, domain expert knowledge, and familiarity with data science methods influence the use and adoption of visual analytics techniques and systems. The goal is to discuss and discover challenges and future directions regarding these issues by proposing design guidelines, empirical findings, and visual analytic techniques.

Visualization ROAR!