Within the last 20 years I worked as a researcher in the fields of robotics, complex systems modeling and simulation, as well as computational neuroscience. I studied computer science at the University of Dortmund, Germany. After finishing my degree I moved to Bremen in order to work at the Robotics Innovation Center (RIC) of the German Research Center for Artificial Intelligence (DFKI). My main line of research there was focused on deep sea underwater robotics. However, I also had the chance to dabble into industrial robotics, autonomous legged robots for space exploration, and brain-computer interfaces. The robotics section of this site highlights some of the work that was done in this context.
The research in Bremen also had some neuroscientific components since the early research of Prof. Dr. Dr. Frank Kirchner (head of the RIC) focused on biologically inspired control of legged robots. These interdisciplinary aspects peeked my interest to such a degree that I became increasingly fascinated by questions of neurobiological information processing. In 2010 Prof. Dr. Gabriele Peters convinced me to join her group at the University of Hagen where I could deepen that fascination. I planned to use numerical simulation to further my understanding of neurobiological information processing. To facilitate this research path I first looked into the general dynamics of complex systems and how to model and simulate them (see complex systems section). Utilizing the results of that research I then focused on modeling and understanding entorhinal grid cells, which are a type of neuron that was discovered only a few years prior to that time.
I was able to find a computational model that is able to describe the behavior of grid cells based on a novel computational principle. In contrast to existing models of grid cells that interpret grid cells as specialized neurons within a system for navigation and orientation, this new model sees grid cells as one instantiation of a much broader principle of computation that is possibly widespread across the entire cortex. You can find more details on this work in the computational neuroscience section of this site. In 2016 I finished my PhD research on grid cells and moved on to apply the core ideas of that research to find a general model of cortical information processing. This research is still ongoing.
Publications
A more comprehensive summary of my publications can be downloaded here.
2021
Efficient Approximation of a Recursive Growing Neural Gas,
In: Computational Intelligence: International Joint Conference, IJCCI 2018 Seville, Spain, September 18-20, 2018 Revised Selected Papers, 2021,
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2020
On the Robustness of Convolutional Neural Networks Regarding Transformed Input Images,
In: Conference: 12th International Conference on Neural Computation Theory and Applications, 2020,
[doi]
2019
Private Reader: Using Eye Tracking to Improve Reading Privacy in Public Spaces,
In: Proceedings of the 21st International Conference on Human-Computer Interaction with Mobile Devices and Services. Taipei, Taiwan: Association for Computing Machinery, Article 18, 2019,
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Challenging the Intuition About Memory and Computation in Theories of Cognition,
In: Proceedings of the 11th International Joint Conference on Computational Intelligence - Volume 1: NCTA, (IJCCI 2019). INSTICC. SciTePress, pp. 522–527, 2019,
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A Possible Encoding of 3D Visual Space in Primates,
In: Computational Intelligence: International Joint Conference, IJCCI 2016 Porto, Portugal, November 9–11, 2016 Revised Selected Papers. Cham: Springer International Publishing, pp. 277–295, 2019,
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A Noise Compensation Mechanism for an RGNG-Based Grid Cell Model,
In: Computational Intelligence: International Joint Conference, IJCCI 2016 Porto, Portugal, November 9–11, 2016 Revised Selected Papers. Cham: Springer International Publishing, pp. 263–276, 2019,
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2018
Simulation von Gitterzellen als Spezialfall eines allgemeinen neuronalen Verarbeitungsprinzips,
In: Springer–Verlag, 2018,
[bibtex]
"Informatik Spektrum" cover
A Survey of Entorhinal Grid Cell Properties,
In: arXiv e-prints, arXiv:1810.07429 (Oct. 2018), arXiv:1810.07429. arXiv: 1810.07429 [q-bio.NC], 2018,
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A Grid Cell Inspired Model of Cortical Column Function,
In: 10th International Joint Conference on Computational Intelligence (IJCCI 2018), Seville, Spain, September 18-20., pp. 204–210, 2018,
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2017
Entorhinal Grid Cells May Facilitate Pattern Separation in the Hippocampus,
In: Proceedings of the 9th International Joint Conference on Computational Intelligence, IJCCI 2017, Funchal, Madeira, Portugal, November 1-3, pp. 141–148, 2017,
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2016
Noise Resilience of an RGNG-based Grid Cell Model,
In: Proceedings of the 8th International Joint Conference on Computational Intelligence, IJCCI 2016, Volume 3: NCTA, Porto, Portugal, November 9-11, pp. 33–41, 2016,
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nominated for best paper award
Modelling the Grid-like Encoding of Visual Space in Primates,
In: Proceedings of the 8th International Joint Conference on Computational Intelligence, IJCCI 2016, Volume 3: NCTA, Porto, Portugal, November 9-11, pp. 42–49, 2016,
[pdf|doi|bibtex]
best paper award
A Sparse Representation of High-Dimensional Input Spaces Based on an Augmented Growing Neural Gas,
In: GCAI 2016. 2nd Global Conference on Artificial Intelligence. Vol. 41. EPiC Series in Computing. EasyChair, pp. 303–313, 2016,
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A Computational Model of Grid Cells based on a Recursive Growing Neural Gas,
In: PhD thesis. University of Hagen, 2016,
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awarded with the Fakultätspreis 2017 for the best scientific work 2016 at the faculty of mathematics and computer science at the University of Hagen
2015
Clustering Hochdimensionaler Daten,
In: Springer–Verlag, 2015,
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"Informatik Spektrum" cover
Analysis of high-dimensional data using local input space histograms,
In: Neurocomputing 169, pp. 272–280, 2015,
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A New View on Grid Cells Beyond the Cognitive Map Hypothesis,
In: 8th Conference on Artificial General Intelligence (AGI), 2015,
[pdf|doi|bibtex]
2014
Supporting GNG-based clustering with local input space histograms,
In: Proceedings of the 22nd European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning. Louvain-la-Neuve, Belgique, pp. 559–564, 2014,
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2013
Exploratory Modeling of Complex Information Processing Systems,
In: ICINCO (1), pp. 514–521, 2013,
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A Computational Model of Grid Cells Based on Dendritic Self-Organized Learning,
In: Proceedings of the International Conference on Neural Computation Theory and Applications, 2013,
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nominated for best paper award
2012
A generalized computational model for modeling and simulation of complex systems,
In: Research Report 4. University of Hagen, 2012,
[pdf|bibtex]
2009
Automatic Workspace Analysis and Vehicle Adaptation for Hydraulic Underwater Manipulators,
In: OCEANS MTS/IEEE Conference (OCEANS-09). o.A., 2009,
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A Multi-Layered Controller Approach for High Precision End-Effector Control of Hydraulic Underwater Manipulator Systems,
In: OCEANS MTS/IEEE Conference (OCEANS-09). o.A., 2009,
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Realtime motion compensation for ROV-based teleoperated underwater manipulators,
In: OCEANS 2009 - EUROPE, 2009,
[pdf|doi|bibtex]
2008
A practical underwater 3D-Laserscanner,
In: Proceedings of the MTS/IEEE Conference on Oceans, Poles and Climate. MTS/ IEEE Oceans. IEEE, 2008,
[pdf|doi|bibtex]
A Robust Vision Based Hover Control for ROV,
In: Proceedings of OCEANS ’08 (MTS) / IEEE KOBE-TECHNO-OCEAN ’08. IEEE, 2008,
[pdf|doi|bibtex]
Sensorless Computer Control of an Underwater DC Manipulator,
In: Proceedings of OCEANS ’08 (MTS) / IEEE KOBE-TECHNO-OCEAN ’08. IEEE, 2008,
[pdf|doi|bibtex]
Robust Vision-Based Semi-Autonomous Underwater Manipulation,
In: The 10th International Conference on Intelligent Autonomous Systems. IOS Press, pp. 308–315, 2008,
[pdf|doi|bibtex]
2007
Höhenbildbasierte Segmentierung,
In: Springer–Verlag, 2007,
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"Informatik Spektrum" cover
Sensor Processing and Behaviour Control of a Small AUV,
In: Autonome Mobile Systeme AMS 2007- 20. Fachgespräch Kaiserslautern. Robotics Research Lab of the University of Kaiserslautern. Kaiserslautern, Germany: Springer, pp. 327–333, 2007,
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A Topology-Independent Similarity Measure for High-Dimensional Feature Spaces,
In: Artificial Neural Networks. 17th International Conference (ICANN 2007). Vol. 4669. LNCS Part 2. Porto, Portugal: Springer, pp. 331–340, 2007,
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Image Segmentation Based on Height Maps,
In: Computer Analysis of Images and Patterns. Vol. 4673. Lecture Notes in Computer Science. Springer Berlin Heidelberg, pp. 612–619, 2007,
[pdf|doi|bibtex]
Design of a μAUV,
In: Proceedings of the 4th International AMiRE Symposium (AMiRE-2007). Buenos Aires, Argentinien: Heinz Nixdorf Institut Universiät Paderborn, pp. 99–106, 2007,
[pdf|bibtex]
best paper award
C-Manipulator: An Autonomous Dual Manipulator Project for Underwater Inspection and Maintenance,
In: Proceedings of OMAE 2007. ASME 2007 International Conference on Offshore Mechanics and Arctic Engineering. San Diego, USA, 2007,
[pdf|doi|bibtex]
2006
Dynamisches Lernen von Nachbarschaften zwischen Merkmalsgruppen zum Zwecke der Objekterkennung,
In: diploma thesis, University of Dortmund, 2006,
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2005
Decentral control of a robot-swarm,
In: Autonomous Decentralized Systems, 2005. ISADS 2005. Proceedings, pp. 347–351, 2005,
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2004
Virtual Robot: Automatic Analysis of Situations and Management of Resources in a Team of Soccer Robots,
In: Tech. rep. PG 442 Final Report. University of Dortmund, 2004,
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Virtual Robot - Adaptive Ressource Management in Robot Teams,
In: Technical Report 0204. presented at International RoboCup Worldchampion, Lissboa, July 2004. University of Dortmund, 2004,
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