Benjamin Aranda, assistant professor in The Irwin S. Chanin School of Architecture, and Sam Keene, professor of electrical engineering and John and Mary Manuck Distinguished Professor of Design, have co-authored an article exploring the intersections of art, architecture, and engineering through a collaborative teaching model that uses generative algorithms to push the boundaries of creative practice. 

Titled "Generative Algorithms for Art and Architecture: A Collaborative Teaching Approach," their work was published in a recent issue of Tradition-Innovations in Arts, Design, and Media Higher Education and presents outcomes of a course they co-teach at Cooper called Generative Algorithms for Art and Architecture. The course, which is offered to students from all three schools at Cooper, emphasizes the importance of interdisciplinary collaboration, combining technical expertise with artistic vision to solve complex problems. 

"Our work contributes to the long-term understanding of AI in the arts and design in higher education because we have developed a successful course model focused on collaboration between creatives and technologists that can be replicated at other institutions," Aranda and Keene explain. Their article explores this approach to merging art and architecture practices with technological research as a means of engaging students in the broader pedagogical, creative, and ethical implications of generative algorithms and machine learning.

"We found that students often defy expectations defined by their discipline," report Aranda and Keene. "For instance, engineers developed highly artistic creative concepts, while artists and architects suggested solutions to technical challenges."