Join Professor Pier Luigi Dragotti for Science Breaks: When art meets science, the algorithms that revealed Leonardo’s hidden drawings, to hear about his AI augmented chemical analysis of Leonardo Da Vinci’s Virgin of the Rocks.
The heritage sector is experiencing a digital revolution through the use of advanced optical, infrared and x-ray imaging as well as spectroscopic techniques that map the chemical elements in paintings. These provide a non-destructive way to capture new information about paintings, including secrets hidden underneath the surface layers.
This new information is helping art historians reinterpret and better contextualise their collections. However new digital analysis techniques often come with reams of data to interpret. AI algorithms clever enough to understand the physics of how the data was collected may provide the key to unlocking insights humans alone would struggle to extract
In this talk, Professor Pier Luigi Dragotti will discuss his own AI augmented chemical analysis of Leonardo’s “Virgin of the Rocks”. This project, in collaboration with the National Gallery and University College London, has revealed in great clarity hidden drawings of an abandoned composition.
Pier Luigi Dragotti is Professor of Signal Processing in the Electrical and Electronic Engineering Department at Imperial College London and a Fellow of the IEEE. He received the Master Degree (summa cum laude) in Electronic Engineering from the University Federico II, Naples, Italy, in 1997; and the PhD degree from the Swiss Federal Institute of Technology of Lausanne (EPFL), Switzerland in 2002. He has held several visiting positions at Stanford University, CA in 1996, at Bell Labs, Lucent Technologies, NJ in 2000 and at Massachusetts Institute of Technology (MIT) in 2011.
Professor Dragotti was Technical Co-Chair for the European Signal Processing Conference in 2012, Associate Editor of the IEEE Transactions on Image Processing. He was also the recipient of an ERC starting investigator award. Currently, he is Editor-in-Chief of the IEEE Transactions on Signal Processing and a member of the IEEE Special Interest Group on Computational Imaging.
His research interests include sampling theory, wavelet theory and its applications, sparsity-driven signal processing with application in image super-resolution, neuroscience and art investigation.
Science Breaks is a virtual event series showcasing the impact and relevance of Imperial’s research and work taking place at the College.