Professor of Statistics
Department of Mathematics and Statistics
University of Jyväskylä
Email: firstname.lastname@iki.fi
Bluesky: @juhakarvanen.bsky.social
Mastodon: sigmoid.social/@JuhaKarvanen
Science aims to find causal relations.
Scientific studies, both experimental or observational, should be cost-efficient.
Real data are usually incomplete data.
In a project funded by Research Council of Finland 2025-2029 we develop methods of causal inference that take into account uncertainty related to causality, combine different types of data sources, and aim to solve problems related to missing data and selection bias. The developed methods are applied in ecology, health sciences, and business.
Decision analytics utilizing causal models and multiobjective Optimization (DEMO) is a thematic research area at University of Jyväskylä. DEMO focuses on explicit, concrete decision problems that can be presented with mathematical formalism. Predictive analytics, statistical modelling, causal inference, prescriptive analytics and multiobjective optimization are the key elements needed to create a seamless chain from data to decision. Read more
A joint project between University of Jyväskylä and National Institute of Health and Welfare 2013-2017 aimed to solve problems caused by the decline of participation rates in health examination surveys. Read more
|
|