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Kary Främling is a Professor of Data Science at Umeå University, specializing in data analysis and machine learning. He leads the Explainable AI (XAI) team and holds the position of WASP Professor under the Wallenberg AI, Autonomous Systems, and Software Program. Främling's research focuses on Explainable Artificial Intelligence, particularly the concept of 'outcome explanation', which involves elucidating the results, actions, and recommendations made by AI systems such as deep neural networks. His PhD work, completed between 1991 and 1996, developed the Contextual Importance Utility (CIU) method. His research has delved into areas including Intelligent Products, the Internet of Things, and Digital Twin Systems, bridging the gap between AI technologies and their practical applications in everyday life. Främling emphasizes the necessity of explainability in AI, striving to ensure that AI remains 'humane' by being able to communicate its intentions and actions clearly to end-users. He also teaches courses on Data Preprocessing and Visualization.
Requirements are standard for Master's programs across Social Sciences and Humanities at Umeå. English 6 proficiency is the general rule.