Lisa Moren, Professor, Department of Visual Arts and Director, Imaging Research Center
Lisa Moren was awarded the 2026 CIRCA Pedagogy Fellowship which provides two course releases for her to focus on revising course content for ART 379 Digital and Physical Hybrids and ART 390 IRC Fellows towards the establishment of a new interdisciplinary minor in Data Visualization. The goal of redesigning these courses is to prepare undergraduate Visual Arts students with marketable visualization and emerging-media skills while creating a clearer and more inclusive pathway for students to engage with the Imaging Research Center (IRC). To support this, the IRC is responding to a Provost’s IDEA Initiative by developing a new interdisciplinary minor in Data Visualization that will serve both art and science students. Professor Moren will work with Professor Anita Komlodi, Associate Professor of Human-Centered Computing in Information Systems and Associate Director of the IRC, to co-develop coursework that merges the strengths of their respective departments. The minor brings together artists, designers, engineers, scientists, and software developers, forming a shared learning environment that no single academic program can provide on its own. In the broader culture, data plays a central role in addressing challenges from healthcare to climate science, yet the public often finds data abstract or emotionally distant. Even well-done charts and graphs may fail to connect with broad audiences. Artists around the world are responding to this gap by creating data-driven artworks that spark curiosity and translate complex meta-data into a conceptual or sensory experience. Recent examples include transforming DNA sequences into musical scores, generating animations driven by NASA climate datasets, and developing VR/AR/XR experiences that respond to environmental or astronomical data. The proposed minor formalizes this creative-scientific relationship, offering students a structured environment to explore the expressive and communicative possibilities of data.