Mohammad Ghorbani joins Statistics@SLU

Before joining SLU, Mohammad held academic positions at Umeå University, Luleå University of Technology, and the University of Tabriz in Iran. His research focuses on spatial and spatio-temporal statistics, with particular emphasis on point process theory and its applications in areas like environmental science, climate prediction, epidemiology, criminology, image analysis, forestry, and population studies.

He currently integrates machine learning methods with spatio-temporal models, including spatio-temporal birth–death–growth processes for large-scale analysis of tree growth under changing climate conditions, and intensity estimation in complex regions for forest fire datasets. He also develops functional marked Hawkes processes to model earthquake and hurricane data, as well as data-driven models for infectious disease prediction, applied Bayesian data analysis, regression, and other general statistical methods. Mohammad also contributes to the development of R packages for statistical computing.

Find contact information and expert areas for all our consultants at the Statistics@SLU webpage or contact statistics@slu.se.