I am passionate about using data to expand the knowledge base and create value for customers. My philosophy is: the more data the better, but only if the communication is clear and comprehensible. I believe that with relevant and high-quality data, one can solve and automate many complex issues. My background is in civil engineering in health technology, where I have learned that all forms of data have their interesting aspects and relationships, which I find incredibly exciting to discover and gain insight into. This discovery often leads to algorithms that can assist with predictions and automation of workflows, which creates great value for customers – but also for me personally.
During my PhD, I have focused on time series signals, which has provided me with a large toolbox for handling these types of data. This includes efficient storage of time series, visualization of time series, and signal processing as well as classification using neural networks, machine learning, and classic signal processing algorithms.