1. Thomas Heede

    Thomas has been working on combining cutting-edge DNA sequencing with powerful machine learning to develop new methods to recover and analyze genomes of microbes, and link them to environmental data.

  2. Salomey Osei

    Salomey has been working on understanding the role of ensemble’s diversity on modern AutoML methods.

  3. Ioar Casado

    Ioar has been working on PAC-Bayesian bounds.

  4. Luis A. Ortega

    Luis has been working on ensembles of neural networks, developing methods and empirical studies on how diversity and probabilistic modelling improve their predictive performance.

  5. Javier Cozar

    Javier has been working on the development of InferPy and related methods for making deep probabilistic modelling more accessible, contributing together to software design, model formulation, and empirical validation.

  6. Rafael Cabañas

    Rafael has been working on developing probabilistic models that integrate deep neural networks, leading to joint publications on scalable inference, software tools, and uncertainty-aware decision models.