Doctoral candidate Ville Laitinen - UTU Research Portal

Ville Laitinen
Doctoral candidate

Senior Researcher, Data-analytiikka (Tietotekniikan laitos)

velait@utu.fi

Office: 452E

ORCID identifier: https://orcid.org/0000-0002-2653-1673

CV.pdf

Research group webpage

Areas of expertise

Early warning signals, probabilistic modeling, dynamical systems

Biography

I am a doctoral candidate in computer science with background (M.Sc.) in mathematic and physics.

Research

My research interests include probabilistic modeling of dynamical systems, stability properties, early warning signals and related phenomena. My research is mainly motivated by open questions in microbial ecology.

Teaching

Publications

Statistical signatures for adverse events in molecular life sciences (2023) Laitinen Ville
(Doctoral dissertation (article) (G5))
Probabilistic Multivariate Early Warning Signals (2022)
- Lecture Notes in Computer Science
Computational Methods in Systems Biology 20th International Conference, CMSB 2022, Bucharest, Romania, September 14–16, 2022, Proceedings Laitinen Ville, Lahti Leo
(Refereed article in conference proceedings (A4))
Probabilistic early warning signals (2021)
- Ecology and Evolution
Laitinen Ville, Dakos Vasilis, Lahti Leo
(Refereed journal article or data article (A1))
Taxonomic signatures of cause-specific mortality risk in human gut microbiome (2021)
- Nature Communications
Salosensaari Aaro, Laitinen Ville, Havulinna Aki S., Meric Guillaume, Cheng Susan, Perola Markus, Valsta Liisa, Alfthan Georg, Inouye Michael, Watrous Jeramie D., Long Tao, Salido Rodolfo A., Sanders Karenina, Brennan Caitriona, Humphrey Gregory C., Sanders Jon G., Jain Mohit, Jousilahti Pekka, Salomaa Veikko, Knight Rob, Lahti Leo, Niiranen Teemu
(Refereed journal article or data article (A1))
Maternal prenatal psychological distress and hair cortisol levels associate with infant fecal microbiota composition at 2.5 months of age (2020)
- Psychoneuroendocrinology
Aatsinki A, Keskitalo A, Laitinen V, Munukka E, Uusitupa H, Lahti L, Kortesluoma S, Mustonen P, Rodrigues AJ, Coimbra B, Huovinen P, Karlsson H, Karlsson L
(Refereed journal article or data article (A1))
A Hierarchical Ornstein-Uhlenbeck Model for Stochastic Time Series Analysis (2018)
- Lecture Notes in Computer Science
Advances in Intelligent Data Analysis XVII: 17th International Symposium, IDA 2018, ’s-Hertogenbosch, The Netherlands, October 24–26, 2018, Proceedings Laitinen V., Lahti L.
(Refereed article in conference proceedings (A4))