Ms Maria Skoularidou

Contact information

Research interests

During my undergraduate studies in Informatics I was delighted to explore the essentials of information theory and theoretical computer science (algorithmic and Kolmogorov complexity, computability, asymptotic theory). Later, as postgraduate student I focused on Bayesian methods and applications. My fields of interest lie in Bayesian high-dimensional problems, mixture models, clustering and Machine Learning.


1) Kontoyiannis, Ioannis, and Maria Skoularidou. "Estimating the directed information and testing for causality." IEEE Transactions on Information Theory 62.11 (2016): 6053-6067.
2) Heard, Nick, Konstantina Palla, and Maria Skoularidou. "Topic modelling of authentication events in an enterprise computer network." Intelligence and Security Informatics (ISI), 2016 IEEE Conference on. IEEE, 2016.

About us

The Cambridge Centre for Data-Driven Discovery (C2D3) brings together researchers and expertise from across the academic departments and industry to drive research into the analysis, understanding and use of data science.

  • Supports and connects the growing data science research community 
  • Builds research capacity in data science to tackle complex issues 
  • Drives new research challenges through collaborative research projects 
  • Promotes and provides opportunities for knowledge transfer 
  • Identifies and provides training courses for students, academics, industry and the third sector 
  • Acts as a gateway for external organisations 

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