I have no material signature. Through the years of practicing in and out of the academic design cluster I have become adept at applying various research and materialisation tactics to facilitate my inquiries, from building homemade aluminium foundries to multi-material casting and rapid prototyping. I move between large-scale, systemic analysis and ecological research (inspired by Actor Network Theory, among others) and small-scale gestures of testing and production.
I can flesh out the speculative scenarios not just with narrative props, but useful tools and methodologies that can help us probe the boundaries of our desired futures here and now, with verifiable results.

Once a lapsed product designer from Wroclaw (PL), then an alumnus of Design Acadamy Eindhoven (2022), now practicing (erratically) as freelance designer and researcher based in Eindhoven (NL).

Within my practice, I investigate my own entanglement in material ecologies and prototype low-res strategies for living within planetary boundaries. This often happens through material-based inquires, and expresses itself in toolkits, protocols, production setups, objects, exhibitions, text, and other formulations. I tend to work towards outcomes that are non-prescriptive, auto-interrogatory, less-extractive, and ready to appropriate.

Lately, I have been exploring the notion of ‘metabolism’ in the context of design production and exhibition-making (with support of Creative Industries Fund NL). My ongoing and past collaborations include Katrin Hornek (A), envisions (NL), and Medialab Matadero.

As a designer and researcher, I:

1. Prototype material strategies / practices / tools for living within planetary boundaries.

2. Disentangle / re-entangle with material ecologies (find them ontologically interesting, they serve as case studies) ~ metabolic outlook

3. Criticality interrogate the entanglement of design in the polycrisis and thinking about decoupling

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Metabolic production - a caloric and spiritually ecological perspective on design processes

Non-extraction, harmlessness

The idea of computational space or self-computing space stresses, in particular, that the algorithms of machine learning and AI are emergent systems that are based on a mundane and material division of space, time, labor, and social relations. Machine learning emerges from grids that continue ancient abstractions and rituals concerned with marking territories and bodies, counting people and goods; in this way, machine learning essentially emerges from an extended division of social labor. Despite the way it is often framed and critiqued, artificial intelligence is not really “artificial” or “alien”: in the usual mystification process of ideology, it appears to be a deus ex machina that descends to the world like in ancient theater. But this hides the fact that it actually emerges from the intelligence of this world.