Research coordinator
Lund University
Lund, Skane Lan, Sweden
In my previous research, I have worked in various fields, including lipid synthesis in Mycoplasma pneumoniae, where I discovered how certain auto-immunogenic lipids that can cause Guillain-Barré syndrome are produced in this bacterium. I also worked on fold prediction modeling of glycosyltransferases in bacteria, using multivariate sequence analysis based on mathematics. After completing my PhD, I continued to Karolinska Institutet with a postdoctoral fellowship, focusing on inflammatory processes in atherosclerosis.
I have personal experience living with chronic pain, which began following an injury. This experience led me to conceive the idea for Paindrainer using knowledge from my previous research, while grappling with the adjustments needed to manage my condition. Meeting others enduring similar challenges reinforced my recognition of the need for a more person centric approached to self-management of pain. The idea of Paindrainer is based on the principle that if advanced mathematics can be used for protein fold predictions, it should be possible to calculate , by AI optimal ways to plan my day that is based on my specific needs and abilities.
My main research interest is improving the self-management of pain through digital tools and real-world evidence.
Disclosure information not submitted.