David Stork – CUDAN Lecture

When: 2026-02-16 16:00-17:30 (Tallinn time)
Where: A108 & online

The event is public via zoom:
https://zoom.us/j/94629959885?pwd=2NktNsXm0SzbzwwmfGbqlk5UZQoARw.1
Meeting ID: 946 2995 9885 Passcode: 007238

Speaker

David G. Stork
Adjunct Professor, Stanford University, United States

Lecture title

When Computers look at art: Recent triumphs and future opportunities for computer-assisted connoisseurship of fine art paintings and drawings.

Abstract
Our cultural patrimony of fine art paintings and drawings comprise some of the most important, memorable, and consequential images ever created, and present numerous problems in art history and the interpretation of ‘authored’ stylized images. While sophisticated imaging (by numerous methods) has long been a mainstay in museum curation and conservation, it is only in the past few years that true image analysis—powered by computer vision, machine learning, and artificial intelligence—have been applied to fine art images. Fine art paintings differ in numerous ways from the traditional photographs, videos, and medical images that have commanded the attention of most experts up to now: such paintings vary extensively in style, content, non-realistic conventions, and especially intended meaning.
Rigorous computer methods have outperformed even seasoned connoisseurs on several tasks in the image understanding of art, and have provided new insights and settled deep disputes in art history. Additionally, the classes of problems in art analysis, particularly those centered on inferring meaning from images, are forcing computer experts to develop new algorithms and concepts in artificial intelligence.
This talk, profusely illustrated with fine art images and computer analyses, argues for the new discipline of computer-assisted connoisseurship, a merger of humanist and scientific approaches to image understanding. Such work will continue to be embraced by art scholars, and addresses new grand challenges in artificial intelligence.

Bio
David G. Stork, PhD is Adjunct Professor at Stanford University and a graduate in Physics from MIT and the University of Maryland; he also studied Art History at Wellesley College. He is widely recognized as the founder of the field of computer-assisted connoisseurship—the use of sophisticated algorithms for addressing problems in the history and interpretation of fine art—as he wrote some of the earliest papers in the field, co-founded its first conference (now called Computer Vision and Analysis of Art, CVAA), taught the world’s first courses (at Stanford University), and published its first book, Pixels & paintings: Foundations of computer-assisted connoisseurship (Wiley). He has held faculty positions in Physics, Mathematics, Computer Science, Statistics, Electrical Engineering, Neuroscience, Psychology, Computational Mathematical Engineering, Symbolic Systems, and Art and Art History variously at Wellesley and Swarthmore Colleges, Clark, Boston, and Stanford Universities, and the Technical University of Vienna. He is a Fellow of seven international societies and published 220+ scholarly articles, and 64 US patents, and is completing his 10th book on ‘Principled art authentication: A probabilistic foundation for representing and reasoning under uncertainty’.

Links
https://mse.stanford.edu/people/david-stork
https://scholar.google.de/citations?user=D6k9CV8AAAAJ