Modern data analysis from theory to practice
We carry out research on theory, methods and applications of modern statistical and algorithmic data analysis, blending elements from various fields including statistical machine learning/AI, probabilistic programming, numerical ecology, and data science among others.
Our focus is on data-rich applications ranging from molecular life sciences to computational history. The research 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.
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, complementary 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.
Gut microbiota composition is associated with temperament traits in infants by Aatsinki et al. is out!23 May 2019
Presentation in Reading culture and libraries in change conference, Turku17 May 2019
Reconstructing Intellectual Networks - From the ESTC bibliographic metadata to historical material is out - best paper award DHN2019!15 May 2019
Digital Humanities Hackathon DHH'19 ongoing in Helsinki