Research Catalogue

GOON In 2023, at the age of 28, I was diagnosed with testicular cancer. This life-altering event led me to take a closer look at my sexual desire, question my relationship with my genitals, and rethink how I perceive my gender identity. Today, as I navigate a healing period, I seek to explore sensuality as a space of resistance and emancipation. GOON is an attempt to free myself from the shame surrounding (my) queer sexualities. GOON is a research performance inviting the audience to look up close at the way they see and seek pleasure. With a choreographic approach, I am researching queer eroticism as a place of joy. Ignoring the constraints of sexual norms, this exploration focuses on shaping a body that is both playful and desired, despite its apparent dirtiness.

A visual map of the RC. Hover over a screenshot to see the title and author. If you click you will see a gallery with a screenshot of each of its weaves. There is a form which allows you to filter based on title, author, keywords, abstract and date. For an exposition to appear in this map, it needs to be public (share -> public or published). The map is updated once every 24 hours. There is an alternative map that allows you to browse all research by keyword.

This exposition reflects on how machine learning can be integrated with algorithmic composition and live coding to expand digital music creation. The research examines how ML-driven sound analysis, training data, and interactive models reshape compositional workflows. By viewing machine learning as an interpretative and generative process rather than a mere tool, this project challenges conventional boundaries between data gathering, system design, and artistic practice. The discussion is framed through experimental approaches that merge sound synthesis, live coding, and model training, questioning how algorithmic systems can act as both agents of composition and reflective mirrors of musical intention. Through the interplay of structured data, generative models, and exploratory workflows, the study situates machine learning within a broader conversation about creativity, computation, and the evolving role of the composer-programmer.

This exposition contains the complete artistic output and accompanying reflective documentation of the artistic research doctoral project I conducted at the University of Music and Performing Arts Vienna between 2021 and 2024. Free improvisation in music offers a unique field for exploring how artistic practices develop through embodied engagement, critical reflection, and collaborative experimentation. This research focuses particularly on the process of practicing within this context, tracing the evolution of specific exercises and preparatory methods. These were initially tested in collaborative projects with other musicians and later refined through a series of workshops. A central theme that emerged throughout this process is the role of reflection—both musical and verbal—as a vital component of artistic development. This realization culminated in the project Performing Reflection, which established a dialogical relationship between musical improvisation and reflective discourse. The work contributes to a deeper understanding of how structured exercises and reflective practices can support and expand the art of free improvisation, offering new perspectives on its preparation, pedagogy, and performance.

This research consists of the artistic and organizational process of creating a workshop called “Experimental music for children”. In this exposition you can read about how I and my fellow musicians created a workshop for children through eight workshop sessions that took place between February 2024 and January 2025. This resulted in an interactive workshop with children about co-creation, exploration and art making. In addition, this research explores how such a project affects my personal artistic development. In this exposition, you can read about the construction and development of the workshops, and how they evolved into a concrete artistic project. The data collected from the workshops was organised through the merging of critical reflection and analysis. The theoretical part of this research is based on literature and observations of experimental music, art for children and similar experimental music projects. These references serve as material for developing and concretising the artistic vision while shaping the project and ensuring its place in the artistic field as well as the realm of educational research.

One of the aspects Jimmie Blanton (1918–42), best known as Duke Ellington’s bassist between 1939 and 1941, has been most praised for is his tone, particularly its loudness, which has been characterised as “outsized,” “resonant,” “roaring,” and “huge.” While Brian Priestley (2009, 85) observed that tone is often “thought of as god-given,” I wanted to understand why and how Blanton’s tone was (perceived as being) different from that of his peers. I examined several possible impact factors, such as his performance technique and instrument, but found none differed significantly from those of his fellow bassists. Eventually, I (partially) found the answer by recreating Blanton’s music. In this exposition, I examine an experimental recording session by the Brussels Jazz Orchestra and myself on bass in which we recreated the circumstances of a 1930s–1940s Ellington performance, both live and in the studio, in a historically informed way, for example, by using historically appropriate instrumentation, repertoire, location, recording set-up, and performance practice. The outcome revealed that specific changes in the orchestra’s seating plan were key to Blanton’s perceived superior tone. Using media samples, I review the preparation, recording process, and results, drawing on a combination of visual analysis of historical photographs, complete participant observation, comparative auditory analysis, and formal and informal (semi-structured) interviews with participants.