Leo Lahti
Professor
leo.lahti@utu.fi +358 29 450 2390 +358 50 436 4626 Vesilinnantie 5 Turku Office: 452E ORCID identifier: 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
- Gut microbiome and atrial fibrillation: results from a large population-based study (2023)
- EBioMedicine
(A1 Refereed original research article in a scientific journal) - Gut microbiota composition and function in pregnancy as determinants of prediabetes at two-year postpartum (2023)
- Acta Diabetologica
(A1 Refereed original research article in a scientific journal) - Impacts of maternal microbiota and microbial metabolites on fetal intestine, brain, and placenta (2023)
- BMC Biology
(A1 Refereed original research article in a scientific journal) - Machine learning approaches in microbiome research: challenges and best practices (2023)
- Frontiers in Microbiology
(A2 Refereed review article in a scientific journal ) - Maternal microbiota communicates with the fetus through microbiota-derived extracellular vesicles (2023)
- Microbiome
(A1 Refereed original research article in a scientific journal) - miaSim: an R/Bioconductor package to easily simulate microbial community dynamics (2023)
- Methods in Ecology and Evolution
(A1 Refereed original research article in a scientific journal) - Microbiome-based risk prediction in incident heart failure: a community challenge (2023) Erawijantari PP, Kartal E, Liñares-Blanco J, Laajala TD, Feldman LE, Carmona-Saez P, Shigdel R, Claesson MJ, Bertelsen RJ, Gomez-Cabrero D, Minot S, Albrecht J, Chung V, Inouye M, Jousilahti P, Schultz JH, Friederich HC, Knight R, Salomaa V, Niiranen T, Havulinna AS, Saez-Rodriguez J, Levinson RT, Lahti L; FINRISK Microbiome DREAM Challenge and ML4 Microbiome Communities
(Other publication) - The gut microbiome is a significant risk factor for future chronic lung disease (2023)
- Journal of Allergy and Clinical Immunology
(A1 Refereed original research article in a scientific journal) - The preterm gut microbiota and administration routes of different probiotics: a randomized controlled trial (2023)
- Pediatric Research
(A1 Refereed original research article in a scientific journal) - What are patterns of rise and decline? (2023)
- Royal Society Open Science
(A2 Refereed review article in a scientific journal ) - An Infancy-Onset 20-Year Dietary Counselling Intervention and Gut Microbiota Composition in Adulthood (2022)
- Nutrients
(A1 Refereed original research article in a scientific journal) - Can gut microbiota throughout the first 10 years of life predict executive functioning in childhood? (2022)
- Developmental Psychobiology
(A1 Refereed original research article in a scientific journal) - Combined effects of host genetics and diet on human gut microbiota and incident disease in a single population cohort (2022)
- Nature Genetics
(A1 Refereed original research article in a scientific journal) - Comprehensive biomarker profiling of hypertension in 36 985 Finnish individuals (2022)
- Journal of Hypertension
(A1 Refereed original research article in a scientific journal) - COMPREHENSIVE BIOMARKER PROFILING OF HYPERTENSION IN 36,985 FINNISH INDIVIDUALS (2022)
- Journal of Hypertension
(Other publication) - Distinct Diet-Microbiota-Metabolism Interactions in Overweight and Obese Pregnant Women: a Metagenomics Approach (2022)
- Microbiology spectrum
(A1 Refereed original research article in a scientific journal) - Early prediction of incident liver disease using conventional risk factors and gut-microbiome-augmented gradient boosting (2022)
- Cell Metabolism
(A1 Refereed original research article in a scientific journal) - Enhancing biomarkers with co-abundance (2022)
- Nature Computational Science
(B1 Non-refereed article in a scientific journal) - FdeSolver: A Julia Package for Solving Fractional Differential Equations (2022)
- arXiv.org
(Other publication) - Gut Microbiome Composition Is Predictive of Incident Type 2 Diabetes in a Population Cohort of 5,572 Finnish Adults (2022)
- Diabetes Care
(A1 Refereed original research article in a scientific journal)