Hans Salomonsson has during his career in industry and academia implemented, applied and improved many types of machine learning algorithms, e.g. deep learning (LSTM, CNN, Deep Reinforcement Learning), decision tree based models (RF, GBM), SVM, etc., in many different programming languages, e.g. C, C++, C#, Python, R, Java, Scala, Objective-C, MATLAB and Julia. He enjoys taking state of the art machine learning research and adapting it to solve particular research and business problems. Alongside his engineering physics studies he also studied industrial and financial management and is passionate about the opportunities data-driven algorithms have on business processes and strategy.