Bruno Cornelis obtained a Ph.D. degree in Applied Sciences (awarded with highest honors) from VUB in 2014. During his Ph.D with the department of Electronics and Informatics (ETRO) he investigated the use of various image processing tools in support of art scholarship. His research interests include statistical data analysis and sparse representations in computational imaging applications. In the period of 2014-2015 he was a visiting assistant professor at the Mathematics Department of Duke University. From 2016 onwards he is a guest professor at ETRO. Since April 2018, he became a data scientist for the company Macq, while keeping a 20% appointment as guest professor. Macq is a Brussels-based company, and a leading expert in the field of smart mobility. Since 2020, he became leader of the Camera and Data Science units of Macq, where he oversees the development of the computer vision algorithms deployed on the Macq smart cameras and the analysis of traffic data coming from heterogeneous data sources (e.g. ANPR cameras, inductive counting loops, etc.).
Image processing for art investigation
Computer processing of digital images of paintings has become a fast growing and challenging field of research during the last few years. Our contribution to this research field consists of a set of tools that are based on dimensionality reduction, sparse representations and dictionary learning. These tools are used to assist in art related matters such as restoration, conservation, art history, material and structure characterization, authentication, dating and even style analysis. Since paintings are complex structures the analysis of all pictorial layers and their support requires a multimodal set of high-resolution image acquisitions.