Modern data analysis from theory to practice
We carry out research on theory, methods and applications of modern algorithmic data analysis, blending elements from various fields including statistical machine learning/AI, probabilistic programming, data science, and information engineering.
Our methodologically oriented research is motivated by data-rich applications that range from molecular life sciences to computational history. The team is led by PI Leo Lahti who coordinates the Computational biosciences group in University of Turku, Finland. We are also founding members and part of Helsinki Computational History Group, and have active networks with data science companies and public organizations.
There is a great demand for targeted algorithmic methods to extract information and insights from data with minimal human intervention to guide modeling and experimentation. By combining information across multiple sources it is possible to overcome some of the limitations and statistical uncertainties associated with individual data sets. Open research practices play an important role in our all work.
Ecological aspects of microbiome research; Invited talk in Wageningen, The Nethelands.Oct 9, 2019
Invited talk in Consortium of European Research Libraries CERL annual seminar, Göttingen.Oct 1, 2019
Moein Khalighi joins our team, welcome!Sep 21, 2019
Prof Lahti co-opponent for the PhD thesis defense of Mauricio Barrientos-Somarribas at Karolinska, SwedenSep 21, 2019
Review on microbiome data science is now out.