Martin Atzmueller's research interests include Data Science, Artificial Intelligence, Social Sensing, Human Computing and Network Science. His work focuses on how to 'make sense' of complex data and information processes in science and industry by designing and developing approaches, methods and tools for interactive data science and intelligent analytics, leading to computational sensemaking. For instance, this includes the identification of interesting local patterns (e.g., complex structures, exceptional subgroups, and anomalies), predictive modeling, analysis and exploration of complex heterogeneous and multi-modal data, as well as human-machine learning and decision support. By connecting computational approaches with the human cognitive, behavioral, and social contextual perspectives - thus linking technologies with their users - the goal is to augment human intelligence and to assist human actors in all their purposes, both online and in the physical world.