I have worked as a senior lecturer at Kristianstad University for about 10 years and before that I worked for about 10 years for ABB and Ericsson. 

During my time in the industry, I was mainly involved in operational development with tools such as Lean and Six Sigma. In these contexts, I often worked with and analyzed large datasets to understand, model and predict different variables of interest. For example, to create a model for the time it takes to install a base station or a model to precict the cost of producing a distribution transformer with certain specifications. The skills I learned in industry have been very beneficial for my later work at the university and in my research. 

During my time as a doctoral student, my research was mainly focused on evaluating how new technologies for identifying goods in supply chains affect the overall efficiency of the logistics system and how these technologies can be used to make the system more robust against disruptions. 

To be able to answer these questions, I mainly worked with discrete-event simulation of different logistics systems and analysis of these simulation models. One of my early case studies was analyzing how smart sensors in recycling containers can be used to increase the efficiency in transporting and emptying of full containers. That study has later also led me to do studies that looked into various behavioral aspects of recycling. Since I have a long background of working practically with modeling of data in different contexts, statistics and machine learning are tools that I am well acquainted with and work with in my various research projects.