Heidi Rautiainen

Research skills: Working with collection, handling, and analysing large data sets of (GPS and acceleration) data in R, QQIS and Anaconda, with main interest in spatial modeling and machine learning. Co-production of knowledge with stakeholders, both by individual interviews (using thematic content analysis approach) and workshops. 

Research acticivites: In the organizing committee for Arctic Ungulate Conference, Jokkmokk, 2019 and in the organizing and scientific committee for Reindeer Husbandry Conference, Alta, 2025. 

Teaching (mainly reindeer biology, husbandry, welfare, and diseases) in bachelor and master courses at the Faculty of Veterinary Medicine and Animal Science, SLU:

• Basic science - agriculture and animal science, HV0211
• Ruminant production, HV0210
• Reindeer biology and reindeer husbandry, HV0216
• Animal Environment, BI1200
• Animal nutrition and welfare, HV0201
• Animal husbandry and animal welfare, VM0138

Teaching (R and GIS) in PhD courses Data handling and high-quality illustrations for publications (P000085) and Animal movements - from free ranging to restricted indoor environments (P000012), with focus on spatial data handling and modelling in R.

Defining and evaluating “grazing peace” of reindeer in relation to disturbances. REINPEACE (2026-2029, project leader: Heidi Rautiainen, funded by: Formas)

Samordning av forskningsprojekt ren och renskötsel (2025-2026, project leader: Heidi Rautiainen, funded by: The Swedish Transport Administration)

Sensor-based behavioral recognition in reindeer: improved precision with magnetometer and gyroscope (2026, project leader: Heidi Rautiainen, funded by: KSLA, 2026)

RAInHerd: Drone and AI-Based snalysis of teindeer herd structure, habitat use, and forage-driven movement ecology (2026-2030, project leader: Sven Adler, funded by: Formas)