Tiffany Calvert

Tiffany Calvert’s paintings incorporate diverse technologies, including fresco, 3D modeling, and data manipulation. In Calvert’s work, painting grapples with its digital counterpart - trying to disguise itself into digital imagery while at the same time differentiating itself as material, human and tangible. John Yau, in his Hyperallergic profile, compares their “improvisational riffs and fractured views” to de Kooning.

Calvert’s most recent body of work employs a custom machine learning model developed in collaboration with the computer engineers at WashU’s McKelvey School of Engineering. The model uses a dataset of over 600 historical still life paintings to generate new invented images. Because the dataset is tiny relative to most ML models, the images are mutant, revealing inherent flaws in AI learning. After printing the image at large scale, Calvert paints thickly onto them - the colors are matched to disguise themselves into the reproduction, while the thick impasto imparts a tangible, visceral weight.

Calvert’s work has been exhibited at the Lawrimore Project (Seattle, Wash.), E.TAY Gallery (N.Y.), the Speed Museum (Louisville, Ky.), the Susquehanna Art Museum (Pa.), and Cadogan Contemporary (London, U.K.), among others. Residencies include the Djerassi Resident Artists Program, I-Park, and ArtOmi International Arts Center where she received a Geraldine R. Dodge Fellowship. Calvert has received grants from the Great Meadows Foundation and the Pollock-Krasner Foundation. Prior to coming to WashU in 2024, Calvert served as an associate professor at the University of Louisville. 

Calvert earned a BA in Art from Oberlin College and an MFA from Mason Gross School of Art at Rutgers University.