My research interest is located in between artificial intelligence, cognitive psychology, and computational neuroscience. Here, I aim to explore the computational principles in the brain to foster our fundamental understanding of the brain’s mechanisms but also to exploit them in developing intelligent systems. In particular, I look into the processes and mechanisms in the brain that form representations in multi-modal integration and in temporal composition as well as decomposition. As a central approach I model artificial neural networks, specifically continuous time recurrent neural networks (CTRNNs) and convolution neural networks (CNNs) on tasks in cognitive development, natural language processing, and machine learning. A specific current focus is on dynamic timescales mechanisms in networks as well as on variational and approximate Bayesian learning schemes.

Publications

https://stefanheinrich.net/publications/

• since 11/2021, Assistant Professor, Computer Science Department, IT University of Copenhagen, Denmark
• 03/2020–10/2021, Postdoctoral Fellow, International Research Center for Neurointelligence, The University of Tokyo, Japan
• 01/2020–10/2021, External Research Fellow, Knowledge Technology research group, Department of Informatics, Universität Hamburg, Germany
• 04/2016–12/2019, Postdoctoral Research Associate, Sonderforschungsbereich/Transregio Project TRR 169 Crossmodal Learning, Universität Hamburg, Germany, with Tsingua University Beijing, China
• 05/2010–03/2016, Research and Teaching Associate, Knowledge Technology research group, Department of Informatics, Universität Hamburg, Germany
• 06/2006–03/2010, Student Assistant, Polymer Engineering Institute, University of Paderborn, Germany
• 10/2003–10/2009, Studies in Computer Science and Psychology, University of Paderborn

• 20.06.2016, Dr. rer. nat. (German PhD) in Computer Science at Universität Hamburg (Thesis), Germany
• 27.10.2009, Diplom-Informatiker (German MSc) at the University of Paderborn (Thesis), Germany