Leonardo Impett is an assistant professor in Digital Humanities in the Faculty of English at the University of Cambridge. He was previously based at EPFL and Durham University. He has a background as a computer scientist and now works on computer vision-powered art history and on art historical approaches to bias in computer vision systems. Alongside his research in digital art history, he frequently works with machine learning in arts and culture, including for the Liverpool Biennial, the Royal Opera House, and the Whitney Museum of American Art.

Leonardo is interested in supervising doctoral projects in the following areas: computational and quantitative approaches to art and cultural history; critical computer vision, critical AI studies; historical/critical/cultural studies of training datasets and neural architectures; AI in image generation, contemporary art, and curation.

Björn Ommer is a full professor at the University of Munich where he is heading the Computer Vision & Learning Group. Before, he was a full professor in the Department of Mathematics and Computer Science at Heidelberg University and a co-director of its Interdisciplinary Center for Scientific Computing. He received his diploma in computer science from the University of Bonn, and his PhD from ETH Zurich, and he was a postdoc at UC Berkeley.

Björn serves in the Bavarian AI council and has been an associate editor for IEEE T-PAMI. His research interests include semantic scene understanding and retrieval, generative AI and visual synthesis, self-supervised metric and representation learning, and explainable AI. Moreover, he is applying this basic research in interdisciplinary projects within neuroscience and the digital humanities. His group has published a series of generative approaches, including work known as "VQGAN" and "Stable Diffusion", which are now democratizing the creation of visual content and have already opened up an abundance of new directions in research, industry, the media, and beyond.

Hugo Caselles-Dupré is one of Obvious’ three artists. Obvious is a French trio of artists and researchers that uses artificial intelligence algorithms to create works of art. Their work was highlighted in 2018 with the sale of one of their paintings "Edmond de Belamy", the first of its kind, at Christie's NY. Their works, at the crossroads of classical art and the most recent technologies, are subsequently exhibited in the great museums of the world. Obvious aims to bring the tools developed in research to creative people in all industries, in order to initiate the next visual and artistic revolution. Complementary to his artistic career at Obvious, he is an AI researcher with multiple publications in top-tier ML conferences, and he obtained his PhD in Machine Learning from IP Paris (INRIA-ENSTA Paris). Currently, he is leading Obvious Research, a research laboratory on Generative AI (image, video, sound, neurosciences) in partnership with ISIR (Sorbonne University). They are hiring interns, postdocs, research engineers, and PhDs.

Richard Zhang is a Research Scientist at Adobe Research, with interests in computer vision, deep learning, machine learning, and graphics. He obtained his PhD in EECS, advised by Professor Alexei A. Efros, at UC Berkeley in 2018. He graduated summa cum laude with BS and MEng degrees from Cornell University in ECE. He is a recipient of the 2017 Adobe Research Fellowship and was recognized as an Innovator Under 35 by MIT Technology Review in 2023. More information can be found on his webpage: http://richzhang.github.io/.

Yumeng Hou researches and experiments at the intersection of computation, visualisation, and digital cultural archives. Her work explores how data science and digital embodiment can amalgamate to transform and transmit knowledge of intangible cultural heritage, particularly performative and theatrical traditions that embody ideologies associating body and mind. Yumeng completed her PhD in computational museology and digital humanities at the Laboratory for Experimental Museology (eM+), where she explored novel methods for knowledge representation and communication in the context of audiovisual archives and traditional martial arts. Alongside her academic activities, Yumeng has also practised as a creative media technologist and served as a board member for _box lab, a Chinese startup dedicated to innovating data-enhanced exhibitions and playful museums.