Lukas Muttenthaler


PhD student in Machine Learning at the Department of Software Engineering and Theoretical Computer Science, TU Berlin, working on using human inductive biases to align and improve neural network representations, with a focus on low data regimes.

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Research Profile

I am a Student Researcher at Google DeepMind and a PhD student in Machine Learning at TU Berlin and the Berlin Institute for the Foundations of Learning and Data (BIFOLD). I am also a guest researcher in the ViCCo Group at the Max Planck Institute for Human Cognitive and Brain Sciences. I am mainly advised by Klaus-Robert Müller and co-supervised by Martin Hebart, Simon Kornblith, and Andrew Lampinen. During my PhD, I’ve been part of a Research Collaboration between TU Berlin and Google Brain, where I was advised by Simon Kornblith. Previously, I was a MSc student in IT & Cognition / Computer Science of Isabelle Augenstein and Johannes Bjerva at the University of Copenhagen where I mostly worked on Question Answering and Machine Translation.

My research mainly revolves around representation learning. In particular, I am trying to both understand the factors that influence the degree of alignment between human and neural network representations and figure out how we can leverage human inductive biases or insights from cognitive science most fruitfully for (general purpose) machine learning. Have a look at my Google Scholar for more information about my (recent) work. Feel free to reach out to me, if you believe our research intentions are aligned and you are keen to collaborate on a project.

Academic Background