日期： 2026年3月20日 - 2026年3月20日
David Stork will share his insights on how computer vision and machine learning can improve art authentication and connoisseurship. With his many years of experience, he’ll illustrate how image analysis can help distinguish real artworks from forgeries, discuss the strengths and limitations of AI in assigning art, emphasize the importance of using robust statistical methods, and show how computer-assisted techniques can complement traditional connoisseurship. His talk will also highlight the exciting ways in which art historians and computer scientists can collaborate to create trustworthy, understandable tools for art analysis and authentication.
Date: Friday, 20 March, 2026
Time: 6:00–7:00 p.m.
Venue: Drake Gallery, 1/F, Fung Ping Shan Building, UMAG, HKU, 90 Bonham Road, Pokfulam, Hong Kong
Language: English
Please click here to register.
Speaker
David Stork is an Adjunct Professor in two departments and two programs at Stanford University and is widely considered a pioneer in applying sophisticated computer vision and artificial intelligence to problems in the history and interpretation of fine-art paintings and drawings. He published the earliest technical scholarship in the field, taught its first courses (at Stanford), co-founded its first conference (now called Computer Vision and Analysis of Art), and published its first book, Pixels & Paintings: Foundations of Computer-Assisted Connoisseurship (Wiley, 2024). He has lectured at dozens of leading museums worldwide and taught computer methods at the Courtauld Institute of Art in London. He has published over 220 scholarly works and holds 64 issued patents, is a Fellow of eight international professional/scholarly organizations, and is a 2023 Leonardo@Djerassi Fellow. He is completing his tenth book, Principled Art Authentication: A Probabilistic Foundation for Representing and Reasoning under Uncertainty.