Making Sense of Computing in Art

On campus

Dr David G Stork

Tuesday 10 – Friday 13 September 2024
£495

Booking for this course has now closed. You may be interested in one of our evening courses.

Course description

Recently, art historians, conservators and critics have teamed with computer scientists to develop new algorithmic methods for addressing problems in the history and interpretation of art works, primarily of paintings and drawings.

Assuming no expertise in computing, and involving no programming, this course addresses a number of fundamental questions: How do these methods work? What have been their greatest successes, and what are their limitations? How might they evolve, particularly as more and more images and text about art become available online?  Most importantly, how will our understanding of art expand and change as a result of these new tools?

Classroom sessions will be complemented by afternoon visits to relevant collections and research centres. At the end of the course students may also have gained an understanding of how these methods could aid their own art-historical research.

Watch Dr David Stork discuss "Computer Vision, ML, and AI in the Study of Fine Art," a Research Article in the May 2024 CACM.

Computer Vision, ML, and AI in the Study of Fine Art from CACM on Vimeo.

Lecturer’s biography

Dr David G Stork studied Physics at MIT and the University of Maryland, and Art History at Wellesley College. He has held faculty positions in Physics, Mathematics, Computer Science, Statistics, Electrical Engineering, Computation & Mathematical Engineering, Neuroscience, Psychology, and Art and Art History variously at Wellesley and Swarthmore Colleges, Clark, Boston, and Stanford Universities, and the Technical University of Vienna. David has published over 220 peer-reviewed scholarly articles and eight books/proceedings volumes, including Pattern classification (2nd ed.), Seeing the light: Optics in nature, photography, color, vision, and holography; HAL’s Legacy: 2001’s computer as dream and reality, and Pixels & paintings: Foundations of computer-assisted connoisseurship (Wiley, 2023).

Citations