Konstantin Genin

Konstantin Genin is the leader of the Epistemology and Ethics of Machine Learning Research Group within the Cluster of Excellence – Machine Learning for Science at the University of Tübingen, and a member of the Department of Computer Science. His research focuses on the intersection of formal epistemology, machine learning, and statistics, emphasizing topics like inductive inference, algorithmic fairness, causal discovery, and Ockham’s razor. He previously held a postdoctoral fellowship in Philosophy at the University of Toronto, supervised by Franz Huber, and completed his PhD in Logic, Computation, and Methodology at Carnegie Mellon University under Kevin T. Kelly.

Genin’s work employs topological methods to address foundational questions in statistical and machine learning theory. Key contributions include non-circular epistemic justifications for Ockham’s razor, and applications to causal inference and algorithmic fairness. He has presented his research globally, including at institutions like Seoul National University, the University of Milan, and the University of Coimbra. His educational background includes a PhD (2018) and dual BAs in Math and Philosophy (2009) from Brown University.

Genin’s academic contributions span workshops and conferences on philosophy of science, formal epistemology, and machine learning ethics. His research group explores the epistemological challenges and ethical implications arising from machine learning’s role in scientific inquiry and societal decision-making. He maintains active collaborations across disciplines, bridging philosophy, computer science, and statistics.