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.
Lecture on open science and collaboration in digital humanities in University of Turku by Leo LahtiJan 20, 2020
New preprint in medrXiv on Taxonomic Signatures of Long-Term Mortality Risk in Human Gut MicrobiotaDec 23, 2019
Leo Lahti joined as arXiv moderator (applied statistics)Dec 16-20, 2019
Statistical research in microbiome research workshop in Pune, India