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.

Main activities

• Leader of Kernel Methods, Pattern Analysis and Computational Biology (KEPACO) research group
• Vice-Director of Helsinki institute for Information Technology (HIIT)
• Projects:
  • BIODESIGN - Virtual Laboratory for Biodesign. Jane and Aatos Erkko Foundation (2023-2027)
  • MASF - Machine Learning for Systems Pharmacology. Academy of Finland grant (2021-2025)
  • AIB - AI technologies for interaction prediction in biomedicine. Academy of Finland grant (2022-2024)
  • MAGITICS - MAchine learning for diGItal diagnosTICS of antimicrobial resistance. JPIAMR/AoF grant (2020-2022)
• Selection of my publications can be found on the KEPACO group pages and full list in Google Scholar
• My profiles on ResearchGate and Linkedin