I am a research software engineer (RSE) at King’s College London within a newly established central RSE team, and aim to write software that is more reproducible, shareable and allows to more easily build upon existing research incrementally. For me, being an RSE means to contribute to a larger project – that of improving science. I am also a final-stage doctoral researcher in computational neuroscience/complex systems at the Sussex Centre for Consciousness Science, University of Sussex, where I validate information-theoretic measures of complexity and emergence in simulated data to inform empirical applications. Most recently, I’ve leveraged my expertise in complexity science/emergence research for AI safety within a PIBBSS fellowship. See a talk on my research project here.

In the context of my PhD project, I also worked on a Python library to easily apply and compare different measures on different data, in an understandable and comprehensive way including documentation & tutorials. This work has also been part of my mentorship within the Open Seeds mentoring & training program where I have been a mentor myself.

I’ve been a 2023/2024 Software Sustainability Institute (SSI) Fellow aiming to send a strong signal for SSI’s slogan “better software, better research” by providing software development workshops to research communities I’m involved in myself. You can check out (and re-use) material for a research software enginnering tutorial in Python that I’ve created for the Artificial Life conference 2023 in the context of my fellowship.

I have been the main organizer of a symposium on computational approaches to the mind, titled “Rethinking Computational Approaches to the Mind - Fundamental Challenges & Future Perspectives”. Recorded talks and panel discussion can be viewed on YouTube.

I’ve participated in many Brainhacks, and have also been teaching extensively throughout my academic journey so far (subjects included, amongst others, data science and machine learning, including supervising master thesis work, and philosophy).

My academic work so far has been strongly interdisciplinary, intersecting mathematics, machine learning, neuroscience, as well as philosophy. Before starting my doctoral work, I have been investigating information integration in variational inference (still doing so), and looking at embodiment processes in an EEG-based BCI study. I have strong interests in metascience, philosophy of science, moral philosophy, as well as AI safety.

Besides science, I have also been working as a research data scientist in medical education research, teaching assistant for German for refugees, and psychologist for unaccompanied refugee minors. I like volunteering (and have done that most recently at GrowNYC, an environmental sustainability organization in New York).

I do photography and share my work on my photo blog (disctontinued - new work will be posted elsewhere) as well as on Instagram. I also post about (ultra mountain) running, the outdoors more generally & music/culture in the UK/around the world in another account.