Leo Lahti profile picture
Associate Professor, Data-analytiikka
Associate Professor


+358 29 450 2390
+358 50 436 4626
Vesilinnantie 5

Areas of expertise

Data science
Machine Learning
Applied statistics
Statistical programming
Probabilistic models
Complex natural and social systems
Microbial ecology
Computational humanities
Open knowledge


Leo Lahti is associate professor in Data Science in University of Turku, Finland. His research team focuses on computational analysis and modeling of complex natural and social systems. Lahti obtained doctoral degree (DSc) in statistical machine learning and bioinformatics from Aalto University in Finland (2010), developing probabilistic data integration methods for high-throughput life science data. This was followed by subsequent postdoctoral research at EBI/Hinxton (UK), Wageningen University (NL), and VIB/KU Leuven (BE). Lahti has coordinated international networks in data science methods and applications, including e.g. the COST action on statistical and machine learning methods in microbiome studies, and organizes international training events on a regular basis. He is a founder of the open science work group of Open Knowledge Finland ry. For more information, see the research homepage iki.fi/Leo.Lahti


Computational and data science, statistical and probabilistic programming, machine learning, AI, applied statistics, ecological models, open science


Computational scientist focusing on change in complex natural and social systems, and how they can be understood through a computational lens.


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Gut microbiome and atrial fibrillation—results from a large population-based study (2023)

Palmu J., Börschel C.S., Ortega-Alonso A., Markó L., Inouye M., Jousilahti P., Salido R.A., Sanders K., Brennan C., Humphrey G.C., Sanders J.G., Gutmann F., Linz D., Salomaa V., Havulinna A.S., Forslund S.K., Knight R., Lahti L., Niiranen T., Schnabel R.B.
(Vertaisarvioitu alkuperäisartikkeli tai data-artikkeli tieteellisessä aikakauslehdessä (A1))

The gut microbiome is a significant risk factor for future chronic lung disease (2023)

Journal of Allergy and Clinical Immunology
Liu Y., Teo S.M., Méric G., Tang H.H.F., Zhu Q., Sanders J.G., Vázquez-Baeza Y., Verspoor K., Vartiainen V.A., Jousilahti P., Lahti L., Niiranen T., Havulinna A.S., Knight R., Salomaa V., Inouye M.
(Vertaisarvioitu alkuperäisartikkeli tai data-artikkeli tieteellisessä aikakauslehdessä (A1))

Phylogeny-Aware Analysis of Metagenome Community Ecology Based on Matched Reference Genomes while Bypassing Taxonomy (2022)

Zhu Qiyun, Huang Shi, Gonzalez Antonio, McGrath Imran, McDonald Daniel, Haiminen Niina, Armstrong George, Vázquez-Baeza Yoshiki, Yu Julian, Kuczynski Justin, Sepich-Poore Gregory D., Swafford Austin D., Das Promi, Shaffer Justin P., Lejzerowicz Franck, Belda-Ferre Pedro, Havulinna Aki S., Méric Guillaume, Niiranen Teemu, Lahti Leo, Salomaa Veikko, Kim Ho-Cheol, Jain Mohit, Inouye Michael, Gilbert Jack A., Knight Rob
(Vertaisarvioitu alkuperäisartikkeli tai data-artikkeli tieteellisessä aikakauslehdessä (A1))