About
Timo Freiesleben is a Postdoctoral Researcher at the Machine Learning in Science Cluster (University of Tübingen) and an external member of the Munich Center for Mathematical Philosophy (LMU Munich). His work bridges philosophy with machine learning, focusing on interpretable/explainable AI and algorithmic fairness.
Education
- Mathematics
- Philosophy of Science
- Computer Science
- Neuroscience
Research Interests
Freiesleben explores the philosophical foundations of machine learning, emphasizing causality, ethical constraints, and scientific inference from opaque models. His work addresses the epistemological validity of recourse explanations, robustness in AI, and the interplay between human concepts and neural representations.
Recent Publications
His 2021-2025 work spans counterfactual explanations, model robustness, and XAI critique, with methodological innovations like adversarial random forests and improvement-focused causal recourse. Themes include ethical AI deployment in healthcare, feature importance analysis, and philosophical implications of black-box models.
Collaborations & Labs
He collaborates with Dr. Thomas Grote (Tübingen) and was supervised by Prof. Stephan Hartmann (Munich). Affiliated with the Machine Learning in Science Cluster and the Munich Center for Mathematical Philosophy.
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