Dr. Korbinian Schreiber

„What I cannot create, I do not understand.“ Richard Feynman
+49 (0)30 310078 5432

Focus of work

  • Neuromorphic hardware and computational neuroscience
  • Chip design (analog, digital, mixed-signal)
  • New computer architectures and concepts
  • Artificial intelligence and biologically inspired computing
  • Information processing (from the sensor to the cloud)

Curriculum vitae

Korbinian Schreiber studied physics at Ludwig-Maximilians-Universität in Munich, specializing in electronics, biophysics and statistical physics. In addition to his studies, Schreiber worked part-time as a research assistant in various research groups and companies, developing electronic setups and devices. After completing his master's thesis at the German Aerospace Center, he earned his doctorate on accelerated neuromorphic cybernetics at the Kirchhoff Institute of Physics at Heidelberg University. The range of topics covered in his dissertation included chip and board design for analog neuromorphic computers and modeling of biological neural circuits for neuromorphic control of fast robots. Accompanying his teaching activities at Heidelberg University, Schreiber taught as a private lecturer at the Baden-Württemberg Cooperative State University. Since 2021, he has been working as a research associate/consultant at the Institute for Innovation and Technology (iit). He is mainly responsible for research projects in the fields of neuromorphics and new computational concepts.

Teaching assignments

  • Heidelberg University: Electronics for physicists
  • Baden-Wuerttemberg Cooperative State University: Physics for Industrial Engineers

Publications

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Schreiber, Korbinian (2022): Neuromorphe Chips: Künstliche Gehirne aus Silizium?
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Pehle, Christian; Billaudelle, Sebastian; Cramer, Benjamin; Kaiser, Jakob; Schreiber, Korbinian; Stradmann, Yannik; Weis, Johannes; Leibfried, Aron; Müller, Eric; Schemmel, Johannes (2022): The BrainScaleS-2 accelerated neuromorphic system with hybrid plasticity. In: Frontiers in Neuroscience, 16
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Cramer, Benjamin; Billaudelle, Sebastian; Kanya, Simeon; Leibfried, Aron; Grübl, Andreas; Karasenko, Vitali; Pehle, Christian; Schreiber, Korbinian; Stradmann, Yannik; Weis, Johannes (2022): Surrogate gradients for analog neuromorphic computing. In: Proceedings of the National Academy of Sciences, 119, 4
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Billaudelle, Sebastian; Cramer, Benjamin; Petrovici, Mihai A.; Schreiber, Korbinian; Kappel, David; Schemmel, Johannes; Meier, Karlheinz (2021): Structural plasticity on an accelerated analog neuromorphic hardware system. In: Neural networks, 133
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Schreiber, Korbinian (2020): Accelerated neuromorphic cybernetics
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Schreiber, Korbinian; Wunderlich, Timo C.; Pehle, Christian; Petrovici, Mihai A.; Schemmel, Johannes; Meier, Karlheinz (2020): Closed-loop experiments on the BrainScaleS-2 architecture. In: Proceedings of the Neuro-inspired Computational Elements Workshop
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Emmel, Arne; Müller, Eric ; Breitwieser, Oliver; Grübl, Andreas; Ilmberger, Joscha; Karasenko, Vitali; Kleider, Mitja; Mauch, Christian; Schreiber, Korbinian; Schemmel, Johannes (2020): Inference with Artificial Neural Networks on Analog Neuromorphic Hardware. In: IoT Streams for Data-Driven Predictive Maintenance and IoT, Edge, and Mobile for Embedded Machine Learning: Second International Workshop, IoT Streams 2020, and First International Workshop, ITEM 2020, Co-located with ECML/PKDD 2020, Ghent, Belgium, September 14-18, 2020, Revised Selected Papers, 1325, 201, 2021, Springer Nature
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Weis, Johannes; Spilger, Philipp; Billaudelle, Sebastian; Stradmann, Yannik; Emmel, Arne; Müller, Eric; Breitwieser, Oliver; Grübl, Andreas; Ilmberger, Joscha; Karasenko, Vitali (2020): Inference with artificial neural networks on analog neuromorphic hardware. In: IoT Streams for Data-Driven Predictive Maintenance and IoT, Edge, and Mobile for Embedded Machine Learning, 201-212
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Billaudelle, Sebastian; Stradmann, Yannik; Schreiber, Korbinian; Cramer, Benjamin; Baumbach, Andreas; Dold, Dominik; Göltz, Julian; Kungl, Akos F.; Wunderlich, Timo C.; Hartel, Andreas (2020): Versatile emulation of spiking neural networks on an accelerated neuromorphic substrate. In: 2020 IEEE International Symposium on Circuits and Systems (ISCAS)
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Schreiber, Korbinian (2019): Singularität. In: Programmheft des Heidelberger Frühling (S. 88)
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Wunderlich, Timo; Kungl, Akos F.; Müller, Eric; Hartel, Andreas; Stradmann, Yannik; Syed Ahmed; Grübl, Andreas; Heimbrecht, Arthur; Schreiber, Korbinian; Stöckel, David (2019): Demonstrating advantages of neuromorphic computation: a pilot study. In: Frontiers in neuroscience, 13, 260
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Schreiber, Korbinian ; Modest, Heike I. ; Räth, Christoph (2018): Phase walk analysis of leptokurtic time series. In: Chaos: An Interdisciplinary Journal of Nonlinear Science, 28, 6
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Schreiber, Korbinian ; Schemmel, Johannes; Meier, Karlheinz (2017): The Play Pen–Accelerated Embodiment for Accelerated Hardware. In: 1st Human Brain Project Student Conference, 153, 2017
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Zaehringer, Erich; Knapek, Christina; Mohr, Daniel P.; Huber, Peter; Schreiber, Korbinian; Thomas, Hubertus M. (2016): Complex plasma manipulation by segmented electrodes
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Modest, Heike; Räth, Christoph; Schreiber, Korbinian (2016): Phase correlations in nonlinear time series analysis
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Schreiber, Korbinian ; Räth, Christoph (2015): Phase Correlations in Turbulent and Unstable Particle Trajectories