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Alexander Binder

Alexander Binder

Prof. Alexander Binder is Professor for Multimodal Machine Learning at Leipzig University (Germany), Principal Investigator at ScaDS.AI Dresden/Leipzig and Member of the ELLIS Unit Jena. His research focuses on the explainability of complex AI systems, in particular multimodal models that integrate diverse data types such as text, images, audio, and sensor data.
Alex work addresses one of the central challenges of modern artificial intelligence: understanding how and why models make decisions. His research explores issues such as non-causal correlations, adversarial vulnerabilities, and hallucinations in deep learning systems, with the aim of developing more transparent, robust, and trustworthy AI.
He studied mathematics at Humboldt University of Berlin and received his Ph.D. in Computer Science from TU Berlin in 2013 under the supervision of Klaus-Robert Müller. During this time, he co-developed Layer-wise Relevance Propagation (LRP), a widely used method for explaining neural network predictions.
Following academic positions in Oslo, Alex held an assistant professorship at the Singapore University of Technology and Design (2015–2020) and later an associate professorship at the Singapore Institute of Technology.
At Leipzig University, he is building a research group focused on explainable and multimodal AI, contributing both to fundamental research and to teaching in deep learning and machine learning.

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  • Organization
    Leipzig University
  • Profession
    Professor for Multimodal Machine Learning

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