Our main focus is on developing statistical methods for analysing ecological and environmental data and to support environmental management and decision-making. Statistical inference and uncertainty estimation are essential for these fields to ensure that appropriate conclusions and decisions can be reached from experiments and observations.
We are also part of the Research Centre for Ecological Change at the University of Helsinki.
Statistics is a mathematical science with focus on analysis and interpretation of data. It is the traditional data science that is nowadays more important than ever. Statistics research provides tools to analyze data and extract information from it. It plays a central role in almost all fields of modern societies; including the modern change making technologies such as machine learning and artificial intelligence. Statistical methods are also key tools in solving global challenges related to environmental change and globalization.
Our research focuses on hierarchical Bayesian modeling and decision analysis. Specific research areas include spatial and spatio-temporal statistics, Gaussian processes, state-space models, Bayesian optimization, optimal design of observational studies and computational methods.
Environmental sciences include a broad range of scientific fields studying the environment and solutions to environmental challenges. Ecology studies the distribution and abundance of species, and their interactions with other species and the environment. Biodiversity denotes the variety and variability of life. Biodiversity is essential for the well being of human society for which reason understanding biodiversity and ecosystem processes respond to global megatrends and environmental changes is mandatory to understand the subsequent consequences to, for example, food safety and human health.
Our research concentrates on ecological/biodiversity changes and their implications to ecosystem functions and services in general. Specific research lines we have been, and are currently, working on include species distribution modelling, population and fisheries management, uncertainty assessment and data fusion in environmental simulators as well as on environmental management and risk assessment. One of our past main research projects focused on environmental risk assessment in Arctic marine areas.