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
- Skin microbiota diversity among genetically unrelated individuals of Indian origin (2022)
- PeerJ
(A1 Refereed original research article in a scientific journal) - The Anatomy of eighteenth Century Collections online (eCCO)1 (2022)
- Eighteenth Century Studies
(A1 Refereed original research article in a scientific journal) - Towards standardized and reproducible research in skin microbiomes (2022)
- Environmental Microbiology
(A2 Refereed review article in a scientific journal ) - Applications of Machine Learning in Human Microbiome Studies: A Review on Feature Selection, Biomarker Identification, Disease Prediction and Treatment (2021)
- Frontiers in microbiology
(A2 Refereed review article in a scientific journal ) - Corpus Linguistics and Eighteenth Century Collections Online (ECCO) (2021)
- Research in Corpus Linguistics
(A1 Refereed original research article in a scientific journal) - Efficient computation of Faith's phylogenetic diversity with applications in characterizing microbiomes (2021)
- Genome Research
(A1 Refereed original research article in a scientific journal) - Examining the Early Modern Canon: The English Short Title Catalogue and Large-Scale Patterns of Cultural Production (2021) Data Visualization in Enlightenment Literature and Culture Tolonen Mikko, Hill Mark J., Ijaz Ali Z., Vaara Ville, Lahti Leo
(A3 Refereed book chapter or chapter in a compilation book) - Exit time as a measure of ecological resilience (2021)
- Science
(A1 Refereed original research article in a scientific journal) - Gut microbiota diversity but not composition is related to saliva cortisol stress response at the age of 2.5 months (2021)
- Stress
(A1 Refereed original research article in a scientific journal) - Gut microbiota of patients with different subtypes of gastric cancer and gastrointestinal stromal tumors (2021)
- Gut Pathogens
(A1 Refereed original research article in a scientific journal)



