“Moving from Data Visualization to Data-Driven Art”
How can we embrace the objective experience of scientific inquiry and the subjective experience of art? In this talk, Mare Hirsch will discuss her approach to navigating the challenges and opportunities of creating data-driven art–and highlight the way science and art share some complementary perspectives.
Thursday June 30
Mare Hirsch is an artist and researcher currently based in Santa Barbara, California. The work investigates
. data-driven approaches to making art that connect form and information
. machine learning and artificial intelligence as tools for creative practice
. novel materials for fabrication, design, and sculpture
A native of the American Midwest, Hirsch is currently a PhD candidate in the Media Arts & Technology program at UC Santa Barbara. Prior to her doctoral studies, Hirsch completed a bachelor of music at Lawrence University’s Conservatory of Music and a master of music at the Shepherd School of Music at Rice University.
Artist Statement
Through my art and research, I seek to expand conventional methods of creative practice by developing and using artist-centric technologies. To do so, I draw on methods and tools from other domains, such as computer science and engineering, to reimagine technology’s role in art in a way that is inclusive to a broad diversity of media.
My work is often collaborative; I engage with experts in dance, ecology, philosophy, sociology, and physics to reimagine- our collective relationship to data generated by the practice of these fields. I draw connections between form and information through a practice that results in diverse visualizations and communications of knowledge, which inherently span, point out, and reinforce the bonds between seemingly disparate methods of creative thought.
My creative workflow encompasses sculpture, interactive installation art, generative graphics, and sound. The pieces I create, informed as they are with data characterizing real phenomena, are all methods of engaging with, processing, and coming to a deeper understanding of the forces that govern nature, society, and the infinite intersections be- tween the two. This method of understanding complex processes, through the making of experiential art, extends to the greater public by offering a lens through which reflection, discourse, and community-building may occur.
Selected Press
Q&A with Mare Hirsch
Visual artist Mare Hirsch named 2021 Fermilab artist-in-residence
Selected Virtual presentations
What’s Mare Hirsch up to? Artist Chat October 2021
Selected Exhibitions
University of Puget Sound, Kittredge Gallery
Transmorphic Machines – October-December 2022
Precession is a data-driven installation that explores the intangible scales inherent to the Muon g-2 experiment at Fermilab. The 24 light structures and sounds correspond to the 24 calorimeters used in the experiment to measure the precession of muons moving around a 50-foot diameter electromagnetic ring. Precession reimagines the infinitesimally small scale of Muon g-2 through the creation of a space in which light and sound are driven by the experimental data collected by the Fermilab scientists.