معرفی
Markus Ådahl serves as Associate Professor in the Department of Mathematics and Mathematical Statistics at Umeå University, Sweden. His research focuses on developing advanced statistical methodologies for emergency medical services optimization, with primary office location at MIT-huset, plan 3, Matematik och matematisk statistik, MIT.B.349, Umeå.
His work specializes in spatial statistics and machine learning applications for prehospital care systems. Key research areas include spatio-temporal modeling of ambulance demand, composite likelihood intensity estimation, and large-scale forecasting of emergency calls using log-Gaussian Cox processes. This research directly addresses operational challenges in northern Sweden's emergency response infrastructure through data-driven approaches.
Recent publications demonstrate consistent focus on ambulance call pattern analysis, with methodological innovations in regularized semi-parametric modeling (2023) and large-scale spatio-temporal forecasting (2020). These studies establish critical frameworks for optimizing ambulance resource allocation in geographically complex regions.
Ådahl currently leads the long-term research initiative Data-driven optimization of prehospital care via statistics and machine learning (2018-2028), which integrates statistical modeling with machine learning to enhance emergency medical service efficiency. While no formal advisees are listed in available materials, this project coordinates cross-disciplinary collaboration between statisticians, healthcare providers, and emergency response authorities.
