Leo Lahti
Professor
leo.lahti@utu.fi +358 29 450 2390 +358 50 436 4626 Vesilinnantie 5 Turku Työhuone: 452E ORCID-tunniste: https://orcid.org/0000-0001-5537-637X |
Data science; AI; Machine Learning; Applied statistics; Statistical programming; Probabilistic models; Complex natural and social systems; Microbial ecology; Computational humanities; Open knowledge
Leo Lahti is 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) from Aalto University in Finland (2010), developing probabilistic machine learning methods for high-throughput life science data integration. 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 and organizes international data science training events on a regular basis. He is vice chair for the national coordination on open science Finland, executive committee member for the International Science Council Committee on Data (2023-2025), member of the global Bioconductor Community Advisory Board, and founder of the open science work group of Open Knowledge Finland ry. For more information, see the research homepage iki.fi/Leo.Lahti
Computational scientist focusing on change in complex natural and social systems, and how they can be understood through a computational lens.
Computational and data science, statistical and probabilistic programming, machine learning, AI, applied statistics, ecological models, open science
- A toolbox of machine learning software to support microbiome analysis (2023)
- Frontiers in microbiologyFrontiers in microbiology
- Author Correction: Greengenes2 unifies microbial data in a single reference tree (Nature Biotechnology, (2023), 10.1038/s41587-023-01845-1)Maternal microbiota communicates with the fetus through microbiota-derived extracellular vesicles (2023)
- Nature BiotechnologyMethods in Ecology and Evolution
(O2 Muu julkaisu ) - Dealing with dimensionality: the application of machine learning to multi-omics data (2023)
- Bioinformatics
(A2 Vertaisarvioitu katsausartikkeli tieteellisessä lehdessä) - Ebola epidemic model with dynamic population and memory (2023)
- Chaos, Solitons and Fractals
(A1 Vertaisarvioitu alkuperäisartikkeli tieteellisessä lehdessä ) - Gut microbiome and atrial fibrillation: results from a large population-based study (2023)
- EBioMedicine
(A1 Vertaisarvioitu alkuperäisartikkeli tieteellisessä lehdessä ) - Gut microbiota composition and function in pregnancy as determinants of prediabetes at two-year postpartum (2023)
- Acta Diabetologica
(A1 Vertaisarvioitu alkuperäisartikkeli tieteellisessä lehdessä ) - Impacts of maternal microbiota and microbial metabolites on fetal intestine, brain, and placenta (2023)
- BMC Biology
(A1 Vertaisarvioitu alkuperäisartikkeli tieteellisessä lehdessä ) - Machine learning approaches in microbiome research: challenges and best practices (2023)
(A2 Vertaisarvioitu katsausartikkeli tieteellisessä lehdessä) - (2023)
- Microbiome
(A1 Vertaisarvioitu alkuperäisartikkeli tieteellisessä lehdessä ) - miaSim: an R/Bioconductor package to easily simulate microbial community dynamics (2023)
(A1 Vertaisarvioitu alkuperäisartikkeli tieteellisessä lehdessä )



