Research Groups

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AI & Mechanisms

Rediet Abebe

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AI Safety and Alignment

Maksym Andriushchenko

The new AI Safety and Alignment Group focuses on developing technical solutions to reduce risks from general-purpose AI models.

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Science and Probabilistic Intelligence

Maximilian Dax

The group for Science and Probabilistic Intelligence (SPIN) combines foundational research on probabilistic AI with applied research in science.

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Algorithms and Society

Celestine Mendler-Dünner

Building theoretical and practical tools to support responsible and reliable machine learning in social context.

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AutoML

Frank Hutter

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Computational Applied Mathematics & AI Lab

T. Konstantin Rusch

The Computational Applied Mathematics & AI Lab (CAMAIL) is a research group at the ELLIS Institute Tübingen and the Max Planck Institute for Intelligent Systems headed by T. Konstantin Rusch.

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Deep Models and Optimization

Antonio Orvieto

Investigating the interplay between optimizer and architecture in Deep Learning, and new networks for long-range reasoning.

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Empirical Inference

Bernhard Schölkopf

The problems studied in the department can be subsumed under the heading of empirical inference. This term refers to inference performed on the basis of empirical data.

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Robust Machine Learning

Wieland Brendel

We use theoretical and empirical approaches to build machine vision systems that see and understand the world like humans.

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Safety- and Efficiency- aligned Learning

Jonas Geiping

Investigating the feasibility of technical solutions to safety, security in machine learning.