Max Noichl

Hi, I’m Max Noichl! I’m doing a PhD at Utrecht University, where I work in the borderlands between philosophy, computational social science, and digital humanities. I’m advised by Dominik Klein and Erik Stei at the department of theoretical philosophy.

My research explores how foundation models/AI represent the structures which we collectively rely on to make sense of the social world, and how they can become useful tools to understand social processes. This includes work in philosophy of machine learning, e.g. dimensionality reduction & clustering—How can we get hold of these structures in latent space?—in computational social science—Can we run theoretical models of social processes (polarisation, innovation,…), e.g. agent based models, within the structures learned by a language-model?—and in digital humanities—Can we use LLMs to trace the developments of ideas and build data-driven intuitions about macro-processes of science and intellectual history?

In earlier, but ongoing, collaborations I also worked with Johannes Marx on a computational model for collective agency at the University of Bamberg, and Tarja Knuuttila and Andrea Loettgers on computational approaches to the investigation of model transfer at the University of Vienna.

When I’m not working, I play with AI art, make food, or do a little climbing. Some of my side projects can be found under the projects header above. Most are somewhat data-sciency; some also contain philosophy.

As a side job, I also sometimes consult on bibliometric and data science/visualization projects, for example for the European University Institute or the Sozium Bremen. If you have a project of that kind in mind, please feel free to get in touch!

news

Sep 16, 2025	Together with Gregor Bös I’m organizing an autumn school on data-driven methods in philosophy. Join us here!
Sep 12, 2025	Together with Gregor Bös I’m organizing a workshop on data-driven methods in philosophy following the GAP conference in Düsseldorf.
Aug 27, 2025	I’ll be at EPSA 2025 in Groningen, with a poster and a symposium organized together with Hein Duijf.
Jun 15, 2025	I’ll be attending the advanced graduate workshop in computational social science at the Santa Fe institute.
Apr 02, 2025	I’ll be presenting at the workshop: “Large Language Models for the History, Philosophy, and Sociology of Science” in Berlin, April 2-4

selected papers

How Localized Are Computational Templates? A Machine Learning Approach

Maximilian Noichl

Synthese, Mar 2023

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A commonly held background assumption about the sciences is that they connect along borders characterized by ontological or explanatory relationships, usually given in the order of mathematics, physics, chemistry, biology, psychology, and the social sciences. Interdisciplinary work, in this picture, arises in the connecting regions of adjacent disciplines. Philosophical research into interdisciplinary model transfer has increasingly complicated this picture by highlighting additional connections orthogonal to it. But most of these works have been done through case studies, which due to their strong focus struggle to provide foundations for claims about large-scale relations between multiple scientific disciplines. As a supplement, in this contribution, we propose to philosophers of science the use of modern science mapping techniques to trace connections between modeling techniques in large literature samples. We explain in detail how these techniques work, and apply them to a large, contemporary, and multidisciplinary data set (n=383.961 articles). Through the comparison of textual to mathematical representations, we suggest formulaic structures that are particularly common among different disciplines and produce first results indicating the general strength and commonality of such relationships.
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Modeling the Structure of Recent Philosophy

Maximilian Noichl

Synthese, Jun 2021

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This paper presents an approach of unsupervised learning of clusters from a citation database, and applies it to a large corpus of articles in philosophy to give an account of the structure of the discipline. Following a list of journals from the PhilPapers-archive, 68,152 records were downloaded from the Reuters Web of Science-Database. Their citation data was processed using dimensionality reduction and clustering. The resulting clusters were identified, and the results are graphically represented. They suggest that the division of analytic and Continental philosophy in the considered timespan is overstated; that analytical, in contrast to Continental philosophy does not form a coherent group in recent philosophy; and that metaphors about the disciplinary structure should focus on the coherence and interconnectedness of a multitude of smaller and larger subfields.