DH^CH / Valentine Bernasconi

I am currently a PhD student in the field of Digital Visual Studies at the University of Zurich (UZH). Prior to that, I graduated from the Ecole Polytechnique Fédérale de Lausanne (EPFL) with a M.Eng. in Digital Humanities. I also have a previous M.Sc. in Multimedia Design and 3D Technologies from Brunel University London and a B.Sc. in Computer Science from the University of Fribourg, where I received the JAACS award for best Bachelor thesis. The latter was part of an interdisciplinary collaboration with dancers from the University of the Art of Biel (HKB) and engineers from the Haute Ecole d’Ingénierie et d’Architecture of Fribourg (HEIA-FR).

My main research interest lies in between art and technology. Thanks to a minor in art history at the University of Fribourg, I was able to develop a critical approach to artistic content alongside an education in computer science. This interdisciplinary knowledge allowed me to work on a collaborative project called Nautilus. I there investigated the rise of digital media in performing arts from an art history point of view and contributed to the project with an interactive visualization. I further explored the world of augmented reality and 3D experiences with a master thesis called Interactive live 3D visualization. Finally, I had the opportunity to delve into the world of design at the EPFL+ECAL Lab with a master thesis Valorization of visual heritage through A.I. algorithm trained on curated content. The curated content, the poster collection from the Museum für Gestaltung Zürich, allowed me to approach the field from both an art history and artistic perspective and to explore a diversity of computer vision tools. The research lead to the creation of a machine learning model to reproduce the creative thinking of the designer.

The core of my current research is at the intersection of computer vision and art history and is supervised by Prof. Dr. Tristan Weddigen and Dr. Leonardo Impett. I there wish to explore recurrent patterns in pictorial art and their evolution in time and place. This approach relies on the context of visual and cultural influence of artworks and intend to produce new exploring tools to the field of art history.

Computational and Historical Analysis of Hands and Gestures in Early Modern Art.

• Missing annotations: towards automated gesture recognition on artworks