Stefan Heinrich, Ph.D. – Cognitive Developmental Robotics Lab

	Project Researcher, International Research Center for Neurointelligence, The University of Tokyo Email: heinrich.stefan [AT] ircn.jp (B826 6798 4472 ACA0 4986 DF89 3F7E 078F 1EF0 7893) My research interest is located in between artificial intelligence, cognitive psychology, and computational neuroscience. In my research 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 in the brain that form representations in multi-modal integration up to in acquisition of complex cognitive functions. As a central approach I model artificial neural networks, specifically continuous time recurrent neural networks (CTRNNs) and convolution neural networks (CNNs) on tasks in machine learning, natural language processing, and developmental robotics. A particular current focus is on dynamic timescales mechanisms in networks as well as on variational and approximate Bayesian learning schemes. personal page

Project Researcher, International Research Center for Neurointelligence, The University of Tokyo
Email: heinrich.stefan [AT] ircn.jp
(B826 6798 4472 ACA0 4986 DF89 3F7E 078F 1EF0 7893)

My research interest is located in between artificial intelligence, cognitive psychology, and computational neuroscience. In my research 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 in the brain that form representations in multi-modal integration up to in acquisition of complex cognitive functions. As a central approach I model artificial neural networks, specifically continuous time recurrent neural networks (CTRNNs) and convolution neural networks (CNNs) on tasks in machine learning, natural language processing, and developmental robotics. A particular current focus is on dynamic timescales mechanisms in networks as well as on variational and approximate Bayesian learning schemes.

personal page

Career

Career Experience

March 2020 – present	Project Researcher, International Research Center for Neurointelligence, The University of Tokyo, Japan
April 2016 – December 2019	Postdoctoral Research Associate (TRR CML project) with the Knowledge Technology Research Group, Department of Computer Science, University of Hamburg, Germany
May 2010 – March 2016	Research and Teaching Associate of Knowledge Technology Research Group, Department of Computer Science, University of Hamburg, Germany
June 2006 – March 2010	Student Assistant as Developer and Programmer (PSI/REX Simulation Framework Project) of Institute of Polymer Engineering, University of Paderborn, Germany

Education

June 2016	PhD degree in Computer Science (German Doktor der Naturwissenschaften / Doctor rerum naturalium), Department of Computer Science, University of Hamburg, Germany
October 2009	Master degree in Computer Science (German Diplom-Informatiker), subsidiary subject: Psychology, Department of Computer Science, University of Paderborn, Germany

Teaching Experiences

2011 – 2019	Thesis supervision: 8 MSc, 13 BSc
2011 – 2019	Seminar supervision: Bio-inspired Artificial Intelligence, Neural Networks
WS 2011/12 – 19	Project Human–Robot Interaction, every year
2013 – 2016	Support lecture development: Data Mining
2011 – 2016	Support lecture development: Neural Networks
WS 2010/11 – WS 2015/16	Proseminar Artificial Intelligence, every semester
WS 2015/16	Integrated Seminar Knowledge Processing for Intelligent Systems
SS 2014 – SS 2015	Practical tutorial Data Mining, every year
WS 2010/11 – WS 2012/13	Practical tutorial Foundations of Knowledge Processing, every year
SS 2013	Integrated Seminar Knowledge Processing with Neural Networks
SS 2012 – SS 2012	Tutorial Formal Foundations of Computer Science 1, every year
WS 2010/11 – SS 2011	Project Learning and Helping Robots