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graduated as a M.Sc. in Informatics and Multimedia from the University of Augsburg, Germany, in 2007. His areas of interest are Social Signal Processing and Machine Learning, in particular how to close the gap between theory and real life by building real-time recognition systems. He his the founder and core developer of the Social Signal Interpretation (SSI) to which he devoted large parts of his PhD.

joined the Human Centered Multimedia Lab in 2012 after receiving his M.Sc. degree in Informatics and Multimedia from the University of Augsburg, Germany. He is developing software for non-verbal cue detection, in particular he is developing the NOVA tool which allows interactive and cooperative machine learning. His research focuses on automated social attitude detection, such as the engagement in conversations betweens humans and humans-agent systems.

received his M.Sc. degree in Informatics and Multimedia from the University of Augsburg, Germany, in 2009. In 2010 he joined the chair for Human Centered Multimedia of the same University as PhD student. His main interest is the development of fusion algorithms that in real-time combine multi-modal data in a asynchronous manner.

graduated from the University of Augsburg, Germany in 2011. Before graduation, his research area was virtual worlds and autonomous virtual agents where he developed the Advanced Agent Animation (AAA) framework. He is currently active in the field of signal processing where he investigates modern forms of interaction, such as gesture recognition, motion tracking or social cue recognition.

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joined in 2010 after receiving a M.Sc. degree with honors in Computer Science from the Saarland University and working as software engineer at the DFKI GmbH. His research focuses on modeling languages for the interactive behavior of embodied conversational agents and social robots. He developed the VSM software and integrated it with SSI for the realization of serious games in training, coaching and education as well as applications in health- and elderly-care.

graduated in 2013 at the Augsburg University. In his master thesis he explored various noise reduction techniques in audio files to improve recognition robustness in noisy enviroments. He is now developing hardware and software for smart living environments to support elderly people in their homes.

graduated as M.Sc in informatics at Augsburg University in 2014. The main focus of his work is the study of Human Computer Interaction in natural environments. To study Social Signal Processing “in the wild” he is porting SSI to embedded and mobile systems, in particular he added support for Linux and Android systems.

contributed to the SSI Framework since 2014 as a research assistant at the lab for Human Centered Multimedia (HCM). After receiving his M.Sc. degree in Informatics and Multimedia from the University of Augsburg, Germany in 2015, he joined the HCM as a research associate. He’s contributing to the project SenseEmotion, where he uses the SSI Framework to detect physical pain and pain related emotions in biopotentials.

graduated from the Augsburg University in 2015. His focus is on real-time emotion recognition multi-modal input. His work with respect to the SSI involves the deployment of various machine learning techniques for recognizing emotions. Furthermore he explores the possibilities of using SSI as cloud-based service to utilize the framework independently of specific devices or platforms.