1. Browser Art. Navigating with Style

In July 2022, I joined the transdisciplinary team of art historians, computer scientists, designers and software engineers who investigate how artistic browsers, as opposed to commercial browsers, differently configure and display the Internet content. The focus is on uncovering the processual nature of these dynamic visual interfaces and on tracing the underlying algorithmic operations that shape their functionality.

2. Validating Deep-Learning Methods: From Black Hole Imaging to Medical Brain Imaging

Deep learning is a form of artificial intelligence (AI) that uses artificial neural networks, i.e. sets of algorithms hierarchically organised into multiple layers. Instead of being statically programmed, such multilayer networks learn in a data-driven way during a so-called training phase to mathematically characterise and extract underlying patterns of interest from complex data. Once trained and tested for the quality of their performance, deep-learning networks are deployed to extract the pattern of interest from unknown data. Recently, new deep-learning methods are being developed and applied in the context of sparse data measurements to model the missing information from the existing fragmentary measurements. These applications range from black hole imaging to medical neuroimaging. Through a series of case studies, I explore how the nascent field of deep-learning applications in medical brain imaging and black hole imaging is currently negotiating the empirical validity, evidential status and knowledge-producing potential of its evolving methods.

3. From Photography to fMRI: Epistemic Functions of Images in Medical Research on Hysteria

Hysteria, a mysterious disease known since antiquity, is said to have ceased to exist. Challenging this commonly held view, my PhD dissertation examined the current functional neuroimaging research into hysteria and compared it to the nineteenth-century image-based research into the same disorder. My central argument is that, both in the 19th-century and the current neurobiological research on hysteria, images have enabled researchers to generate new medical insights. My analysis goes beyond the surface of the images, focusing on the step-by-step processes of the images’ creation and interpretation in the context of concrete experimental setups.  Through detailed case studies, I trace how different images, from photography to functional brain scans, have reshaped the historically situated medical understanding of this disorder that defies the mind-body dualism. In addition to the completed PhD dissertation, published by transcript Verlag in 2022, the ongoing results of the project comprise multiple peer-reviewed articles.