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
- 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) - Infant fecal microbiota composition and attention to emotional faces (2022)
- Emotion
(A1 Refereed original research article in a scientific journal) - Multi-Trait Genetic Analysis Reveals Clinically Interpretable Hypertension Subtypes (2022)
- Circulation: Genomic and Precision Medicine
(A1 Refereed original research article in a scientific journal) - Phylogeny-Aware Analysis of Metagenome Community Ecology Based on Matched Reference Genomes while Bypassing Taxonomy (2022)
- MSystems
(A1 Refereed original research article in a scientific journal) - Potential pathobionts in vaginal microbiota are affected by fish oil and/or probiotics intervention in overweight and obese pregnant women (2022)
- Biomedicine and Pharmacotherapy
(A1 Refereed original research article in a scientific journal) - Probabilistic Multivariate Early Warning Signals (2022)
- Lecture Notes in Computer Science
(A4 Refereed article in a conference publication ) - Quantifying the impact of ecological memory on the dynamics of interacting communities (2022)
- PLoS Computational Biology
(A1 Refereed original research article in a scientific journal)



