Skip to main content
Assistant Professor in the Department of Computer Science+44 (0) 191 33 44013



I am an interdisciplinary researcher mainly working with methods from machine learning (ML) and artificial intelligence (AI). By building computational models of complex (often cognitive) phenomena I attempt to 1) better understand these phenomena, 2) provide valuable tools for domain experts and end users, and 3) improve the state of the art in ML/AI. Interpretability and robustness is crucial to gain insights and incorporate expert knowledge into the systems.

A focus of my research is on modelling musical structure and perception as a particularly rich and challenging problem. Beyond that, my research includes topics such as the dynamics of communication between agents and the formation of latent/mental representations.

More broadly, I am interested in the development and application of intelligent and autonomous systems, including their social and ethical implications as well as the resulting challenges in arts, legislation and policy making.


Machine Learning & Artificial Intelligence

  • Probabilistic Modelling (Bayesian inference, graphical models, artificial grammars, Monte-Carlo methods, approximate inference)
  • Neuro-Symbolic Modelling (end-to-end differentiable parsing algorithms, deep neural networks, structured differentiable models)
  • Structure Learning (feature discovery, structure learning in graphical models, parsing algorithms)
  • Planning & Decision Making (reinforcement learning, classical planning, Monte-Carlo tree search, heuristic search, active learning)
  • Ethical AI (moral reasoning & autonomous systems)
  • Medicine (3D medical image analysis (CT/MRI) & semi-automatic segmentation)

Cognitive Modelling

  • Music Cognition (perception of harmony & voice leading, hierarchical metrical structure, rhythm, expectation and surprise)
  • Communication & Interaction (emergence of symbols in communication, cultural evolution, iterated learning paradigm)


  • Music (music analysis & musical form, new interfaces for musical expression and education)
  • Vision (natural scene analysis, modelling semantic/relational structure, human character motion prediction)
Short Bio

Before joining Durham University as an Assistant Professor in Computer Science, I worked as a Postdoc in the Digital and Cognitive Musicology Lab at EPFL, Switzerland (2018–2021). I did my PhD in the Machine Learning and Robotics Lab (now Learning and Intelligent Systems Lab) in Stuttgart/Berlin, Germany (2012–2017) after studying Physics and Philosophy at FU Berlin.


Conference Paper

Doctoral Thesis

Journal Article

Other (Print)


Supervision students