FIMM · HiLIFE · University of Helsinki
We develop machine learning methods for biology and medicine: how mutations arise and cause disease, how to predict cancer patient outcomes, and how to make sense of complex, multimodal data. We work in close collaboration with clinicians, biologists and other domain experts.
Meilahti, Helsinki, May 2025Photo: Jouko Siro
What’s new
M.Sc. Prima Sanjaya defends the doctoral thesis "Interpretable deep representation learning of somatic mutations for tumour classification and risk stratification" on 16 October 2026 at 13.00 in Biomedicum 1, Lecture hall 2. Professor Matti Nykter, Tampere University, serves as the opponent.
Alireza Tajmirriahi starts as a doctoral researcher in the FIMM-EMBL rotation program, combining histopathology foundation models with paired spatial transcriptomics data. Welcome!
Guangzhao, Daniyar, Nora, Arina and Hanna presented posters at the 25th European Conference on Computational Biology, Geneva, 31 August - 4 September 2026.
Janne Kantola began his doctoral studies on multimodal histopathology analyses supervised by Tuomas Mirtti, Daniel Laajala and Esa Pitkänen.
Yrjö presented NanoDS, accurate simulation of nanopore sequencing data with distribution approximations, at the IEEE Conference on Computational Intelligence in Bioinformatics and Computational Biology, Athens, 31 August - 2 September 2026.
