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 social sciences and humanities (SSH) research. Turku Data Science Group is led by Associate Prof. Leo Lahti.
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.
Leo Lahti nominated as the Finnish Coordinator and Management Committee member for the COST action on Statistical and machine learning techniques in human microbiome studies.Nov 7, 2019
Research talk at HELDIG Summit, University of HelsinkiNov 6, 2019
Research talk at London Better Science through Better Data organized by Springer Nature and The Wellcome Trust.Oct 29, 2019
Guest lecture on Bibliographic data science in University of Helsinki Digital Humanities courseOct 24, 2019
Presentation at Host-microbiome interactions in health and disease workshop. Wellcome Trust, Hinxton, UK.