About us


  • Strong technical team with background in Machine Learning (ML). Research publicatished in best ML journals and conferences.
  • Team has experience in
    • Genomic prediction of GxE in new environments 1
    • Genomic prediction with high-dimensional phenotypes 2
    • GWAS with high-dimensional phenotypes 3
    • Computer Vision, Image processing
    • Software development
    • Reinforcement learning 4,5
    • Entrepreneurial leadership and innovative products
  • Seed funding from the Finnish Innovation and Technology Fund ( www.businessfinland.fi )
  • Also part of Finnish Center of Artificial Intelligence ( www.fcai.fi )
  • Spin out from Aalto University from Oct 2018


  1. Gillberg et al. Modelling G×E with historical weather information improves genomic prediction in new environments. Submitted. https://www.biorxiv.org/content/early/2017/11/02/213231
  2. Gillberg et al. Multiple Output Regression with Latent Noise. Journal of Machine Learning Research, 17(122):1-35, 2016.
  3. Marttinen et al. Assessing multivariate gene-metabolome associations with rare variants using Bayesian reduced rank regression. Bioinformatics, 30(14):2026-34, 2014.
  4. Wagner, P. A reinterpretation of the policy oscillation phenomenon in approximate policy iteration. In Advances in Neural Information Processing Systems (NIPS), 2011.
  5. Wagner, P. Optimistic policy iteration and natural actor-critic: A unifying view and a non-optimality result. In Advances in Neural Information Processing Systems (NIPS), 2013.