Stefan Heinrich, Ph.D.

東京大学国際高等研究所ニューロインテリジェンス国際研究機構 特任研究員
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.

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経歴

職歴

2020年3月−現在 東京大学国際高等研究所ニューロインテリジェンス国際研究機構 特任研究員
2016年4月−2019年12月 Postdoctoral Research Associate (TRR CML project) with the Knowledge Technology Research Group, Department of Computer Science, University of Hamburg, Germany
2010年5月−2016年3月 Research and Teaching Associate of Knowledge Technology Research Group, Department of Computer Science, University of Hamburg, Germany
2006年6月−2010年3月 Student Assistant as Developer and Programmer (PSI/REX Simulation Framework Project) of Institute of Polymer Engineering, University of Paderborn, Germany

学歴

2016年6月 PhD degree in Computer Science (German Doktor der Naturwissenschaften / Doctor rerum naturalium), Department of Computer Science, University of Hamburg, Germany
2009年10月 Master degree in Computer Science (German Diplom-Informatiker), subsidiary subject: Psychology, Department of Computer Science, University of Paderborn, Germany

教育経験

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
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