Our research focuses on computational analysis of
complex natural and social systems. There is a great demand for
targeted computational techniques to extract information and insights
from rich data collections based on clever combinations of human and
machine intelligence. We blend elements from fields such as machine
learning/AI, probabilistic programming, statistical ecology, and data
science, and drive open developer communities that help to translate
latest theoretical advances into accessible methods to inform
modeling, experimentation, and decision-making. For a full list of publications check this page.
Funding and support
The work has been supported by
- University of Turku
- Academy of Finland
- EU / COST action on Statistical and Machine Learning Techniques in Human Microbiome Studies
- EU / H2020 FindingPheno
- KONE
- Turku University Foundation
- and other sources