I am the leader of the Research Group: Epistemology and Ethics of Machine Learning in the Cluster of Excellence – Machine Learning for Science at the University of Tübingen.

Previously, I was a postdoctoral fellow in Philosophy at the University of Toronto supervised by Franz Huber. My dissertation, supervised by Kevin T. Kelly in Philosophy at Carnegie Mellon, is available here.

This is my CV.   Contact me at konstantin [dot] genin [at] gmail.


Inductive inference, statistics and machine learning, methodology, Ockham's razor, formal epistemology, learning theory, belief revision, topology.

Inspired by formal learning theory, I use topological methods to investigate the inherent complexity of problems in statistics and machine learning. In my dissertation, I give a non-circular epistemic justification for Ockham's razor in statistics and machine learning. I am currently focused on applying these methods to problems in causal inference and algorithmic fairness. Click here for a brief personal research statement. Click here for my research group.


I have an PhD in Logic, Computation and Methodology (Carnegie Mellon, 2018). I have BAs in Math and Philosophy (Brown, 2009).