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Miran Ozdogan

Personal photo - Miran  Ozdogan

Miran Ozdogan

Doctoral Student

Interests

I'm a DPhil student in Computer Science, working in the Neural Processing Lab (PNPL).

Under the supervision of Michael Bronstein and Oiwi Parker Jones I am exploring the application of deep learning to non-invasive brain computer interfaces (BCIs). I previously completed an integrated Bachelors in Computer Science and Statistics at the Ludwig-Maximilians-University of Munich, where I researched the automated optimization of a tree-based reduction method for multi-class classification called nested dichotomy as my final major project. Subsequently, I completed my MPhil in Cambridge where I developed a new tree-based ensembling method that can optimize arbitrary loss functions.

I am particularly interested in:

  • Deep learning approaches for highly noisy data
  • Generative modelling of time-series data

Selected Publications

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Supervisor