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Personal profile

Artistic and research interests

I am interested in developing principled machine learning methods, models and tools for computational and data science. My methods toolbox is primarily built on regularised learning, kernels and sparsity, as well as efficient convex/non-convex optimisation methods. My favourite topics include learning with multiple and structured targets, multiple views and ensembles. Applications of interest include metabolomics, biomedicine, pharmacology and synthetic biology.

Expertise related to UN Sustainable Devlopment Goals

In 2015, UN member states agreed to 17 global Sustainable Development Goals (SDGs) to end poverty, protect the planet and ensure prosperity for all. This person’s work contributes towards the following SDG(s):

  • SDG 3 - Good Health and Well-being
  • SDG 14 - Life Below Water

Education/Academic qualification

Doctoral degree, Engineering and Technology, University of Helsinki

Award Date: 15 Jun 2001

Keywords

  • Algorithms
  • Metabolomics
  • Graph and network data
  • Structured prediction
  • Kernel methods
  • Machine learning

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