Leo Lahti
Professor
leo.lahti@utu.fi +358 29 450 2390 +358 50 436 4626 Vesilinnantie 5 Turku : 452E |
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
- Analytical determination of editions from bibliographic metadata (2019)
- Studia Humaniora Ouluensia
- A National Public Sphere? Analyzing the Language, Location, and Form of Newspapers in Finland, 1771–1917 (2019)
- Journal of European Periodical Studies
- A Quantitative Approach to Book-Printing in Sweden and Finland, 1640–1828 (2019)
- Historical Methods: A Journal of Quantitative and Interdisciplinary History
- Best practices in bibliographic data science (2019)
- Studia Humaniora Ouluensia
- Bibliographic Data Science and the History of the Book (c. 1500–1800) (2019)
- Cataloging and Classification Quarterly
- Gut microbiota composition is associated with temperament traits in infants (2019)
- Brain, Behavior, and Immunity
- Integrating open science in the humanities: the case of computational history (2019)
- Data Dialogues
- Interdisciplinary collaboration in studying newspaper materiality (2019)
- CEUR Workshop Proceedings
- Microbial communities in a dynamic in vitro model for the human ileum resemble the human ileal microbiota (2019)
- FEMS Microbiology Ecology
- Microbiome data science (2019)
- Journal of Biosciences
- Microbiome yarns: The Global Phenotype-Genotype Survey. Episode III: importance of microbiota diversification for microbiome function and biome health (2019)
- Microbial Biotechnology
- Reconstructing intellectual networks: From the ESTC’s bibliographic metadata to historical material (2019)
- CEUR Workshop Proceedings
- Reply to the Letter to the Editor: Gut microbiota composition is associated with temperament traits in infants (2019)
- Brain, Behavior, and Immunity
- Scaling up bibliographic data science (2019)
- CEUR Workshop Proceedings
- The Emerging Paradigm of Bibliographic Data Science (2019) Vaara V, Ijaz A, Tiihonen I, Kanner A, Säily T, Lahti L
- A Hierarchical Ornstein-Uhlenbeck Model for Stochastic Time Series Analysis (2018)
- Lecture Notes in Computer Science
- Digitaaliset ihmistieteet ja historiantutkimus (2018) Menneisyyden rakentajat : teoriat historiantutkimuksessa Mikko Tolonen, Leo Lahti
- Gut Microbiota Composition in Mid-Pregnancy Is Associated with Gestational Weight Gain but Not Prepregnancy Body Mass Index (2018)
- Journal of Women's Health
- Microbial communities as dynamical systems (2018)
- Current Opinion in Microbiology
- microbiome R package (v.3.5) (2018) Leo Lahti, Sudarshan Shetty