Jakub is a computational geographer whose work lies at the intersection of geocomputation, environmental science, and spatial data analysis. His research focuses on developing and applying spatial methods to improve understanding of environmental processes and patterns. A vital part of his work is creating, collaborating on, and improving geocomputational software, with a strong emphasis on reproducibility and accessibility.
He is an active member of the #rspatial community and co-author of the widely used books Geocomputation with R and Geocomputation with Python, which have become key resources for researchers and practitioners in spatial analysis. His contributions span methodological development, software implementation, and applied research in environmental and ecological sciences.
Education & Career
• PhD in Geography, Adam Mickiewicz University, Poland
• Associate Professor, Institute of Geoecology and Geoinformation, Adam Mickiewicz University, Poland
Research Focus
Jakub’s work centres on:
• Development and application of spatial methods for environmental and ecological data
• Geocomputation and the creation of reproducible, open-source spatial workflows
• Integration of spatial statistics, machine learning, and data science for environmental monitoring and modelling
• Improving accessibility and usability of geospatial software tools for research and teaching
Current Projects
• Developing open-source R packages for spatial data analysis and environmental modelling (e.g., spDataLarge, motif, and spatialexplain)
• Advancing reproducible methods for large-scale ecological and environmental datasets
• Co-authoring educational resources and materials to support geocomputation using programming languages
• Collaborating on interdisciplinary projects in ecology, geography, and data science
Professional Consultancy & Teaching
Jakub provides expert training in spatial data science and geocomputation for academic, professional, and applied research projects. He teaches a wide range of topics including:
• Geocomputation with R
• Spatial statistics and modelling
• Environmental applications of spatial analysis
• Reproducible research workflows in R and open-source tools
He also actively contributes to open-source communities and advocates for open, transparent, and collaborative science.
Links
• Website/Blog
• GitHub
• ResearchGate
• ORCID
• Mastodon