Curriculum Vitae - Dr. Raul C. Muresan

First name:
Last name:
Date and place of birth:
Marital status:
Raul Cristian
23.08.1978, Cluj-Napoca, Romania
  • 1993 - 1997: Computer Science High School "Tiberiu Popoviciu", Cluj-Napoca.
  • 1997 - 2002: Technical University of Cluj-Napoca, Faculty of Automation and Computer Science. Graduated in 2002, with a degree exam mark of 10 out of 10.
  • 2002 - 2005: PhD student at Technical University of Cluj-Napoca and since 2004 also at Max Planck Institute for Brain Research and Frankfurt Institute for Advanced Studies. Title of the thesis: "Advanced Neural Modeling for Cortical Processing. From Humans To Machines".
  • 2006 - 2007: Post-Doc at Max Planck Institute for Brain Research and Frankfurt Institute for Advanced Studies, Frankfurt am Main, Germany.
  • Romanian, native
  • Hungarian, fluent
  • English, fluent
  • French, average
  • Italian, average
  • German, beginner
Professional activity:
  • CEO of S.C. Neurodynamics S.R.L.
  • Employee of SC. Nethrom SRL from October 1998 to July 1999, working on database applications for companies from the Netherlands.
  • Employee of SC. NIVIS SRL from September 2002, as a head researcher in Neural Networks technologies.
Scientific activity:
  • Member in the board of directors of the Romanian Institute of Science and Technology (RIST) since 2009.
  • Director of the Experimental and Theoretical Neuroscience Laboratory at the Coneural, RIST in Cluj-Napoca, Romania, since 2007. (Fellow since 2003)
  • Post-Doc at Max Planck Institute for Brain Research and Frankfurt Institute for Advanced Studies, Frankfurt am Main, Germany.
  • Reviewer for Italian Ministry of Health, Estonian Science Foundation, National Research Council.
  • Reviewer for Neural Computation, J Neurophysiology, Frontiers in Neuroscience, Neural Networks, International Journal of Information Fusion
  • Reviewer for Computational Neuroscience Meeting - CNS and International Conference on Artificial Neural Networks - ICANN, 2005 - 2008.
  • Member of the Biology Committee of the National Research Council of Romania (2011-2013).
  • Organizer of the Transylvanian Experimental Neuroscience Summer School (TENSS - ).
Description of scientific work:
  • Dr. Raul C. Muresan’s main work is structured along three main directions. The first one is related to characterizing the dynamics of large-scale neuronal microcircuits, mainly from the point of view of how individual neuronal properties are influencing network dynamics. In this context, resonance and integration are being investigated as different mechanisms involved in excitability, stability and self-sustainability. The second direction is related to analyzing biologically recorded neuronal signals. More concretely, he investigates neuronal codes from the perspective of neuronal readers, by connecting artificial neurons to real recorded neurons. The working hypothesis is "neurons read neurons". Here, his main interest is related to the properties and function of neuronal oscillations, and cortex responses to natural stimuli. The third research direction involves the understanding of the role of oscillations at the perception and cognitive levels. He investigates the expression and role of oscillations, by using EEG, mainly on visual perception tasks.
National and international awards:
  • "Best paper award", Muresan R.C. and Ignat I. (2004), Principles of Design for Large Scale Neural Simulators. Proceedings of the International Conference on Automation, Quality and Testing, Robotics 2004.
  • Grant of the Romanian Government for returning to Romania.
  • Grant of the Romanian Government for assembling a research group and building an EEG lab at Coneural.
  • Grant of the Max Planck Society from Germany: Max Planck - Coneural Partner Group (2008-2011).
  • Grant of the Romanian Government for Young Teams (2010-2013).
  • Grant of the Volkswagen Foundation (20014-2016).
  • Grant of the Romanian Government for Young Teams (2015-2017).
  • European Horizon 2020 PHC 2015 grant (2016-2019).
  • Several grants for funding TENSS: Gatsby Foundation, Wellcome Trust, Romanian Government, Hertie Foundation, The Company of Biologists, EBBS, FENS-IBRO, ONRG etc.
  • Moca V.V., Nikolic D., Singer W., Muresan R.C. (2014), Membrane resonance enables stable and robust gamma oscillations. Cerebral Cortex 24(1):119-142.
  • Pampu N.C., Vicente R., Muresan R.C., Priesemann V., Siebenhühner F., Wibral M. (2013), Transfer Entropy as a tool for reconstructing interaction delays in neural signals, Proceedings of International Symposium on Signals, Circuits & Systems - ISSCS 2013, pp. 1-4.
  • Nikolic D., Muresan R.C., Feng W., Singer W. (2012), Scaled correlation analysis: a better way to compute a cross-correlogram. European Journal of Neuroscience 35(5): 742-762.
  • Moca V.V., Tincas I., Melloni L., Muresan R.C. (2011), Visual exploration and object recognition by lattice deformation. PLoS One 6(7): e22831.
  • Jurjut O.F., Nikolic D., Singer W., Yu S., Havenith M.N., Muresan R.C. (2011), Timescales of Multineuronal Activity Patterns Reflect Temporal Structure of Visual Stimuli. PLoS One 6(2): e16758.
  • Jurjut O.F., Nikolic D., Pipa G., Singer W., Metzler D., Muresan R.C. (2009), A color-based visualization technique for multi-electrode spike trains. Journal of Neurophysiology 102:3766-3778, 2009.
  • Moca V.V., Scheller B., Muresan R.C., Daunderer M., Pipa G. (2009), EEG under anesthesia - feature extraction with TESPAR. Computer Methods and Programs in Biomedicine 95:191-202.
  • Muresan R.C., Singer W., Nikolic D. (2008), The InfoPhase Method or How to Read Neurons with Neurons. Lecture Notes in Computer Science (accepted).
  • Moca V.V., Nikolic D., and Muresan R.C. (2008), Real and Modeled Spike Trains: Where Do They Meet? Lecture Notes in Computer Science (accepted).
  • Nikolic D., Moca V.V., Singer W. and Muresan R.C. (2008), Properties of multivariate data investigated by fractal dimensionality. Journal of Neuroscience Methods 172(1):27-33.
  • Muresan R.C., Jurjut O.F., Moca V.V., Singer W., Nikolic D. (2008), The Oscillation Score: An Efficient Method for Estimating Oscillation Strength in Neuronal Activity. Journal of Neurophysiology 99:1333-1353.
  • Muresan R.C. and Savin C. (2007), Resonance or Integration? Self-sustained Dynamics and Excitability of Neural Microcircuits. Journal of Neurophysiology 97:1911-1930.
  • Lazar A., Muresan R.C., Stadtler E., Munk M., Pipa G. (2007), Importance of electrophysiological signal features assessed by classification trees. Neurocomputing Vol. 70:2017-2021.
  • Florian R.V. and Muresan R.C. (2006), Phase precession and recession with STDP and anti-STDP. Lecture Notes in Computer Science, Vol. 4131, Eds. S. Kollias et al., pp. 718-727, Springer-Verlag Berlin Heidelberg.
  • Savin C., Ignat I. and Muresan R.C. (2006), Heterogeneous networks of spiking neurons: self-sustained activity and excitability. Proceedings of the IEEE 2nd International Conference on Intelligent Computer Communication and Processing (ICCP) 2006.
  • Muresan R.C., Pipa G., Florian R.V., Wheeler D.W. (2005), Coherence, Memory and Conditioning. A Modern Viewpoint. Neural Information Processing - Letters and Reviews, Vol. 7, No. 2, pp. 19-28.
  • Muresan R.C., Pipa G., Wheeler D.W. (2005), Single-unit Recordings Revisited: Activity in Recurrent Microcircuits. Lecture Notes in Computer Science, Vol. 3696, Eds. W. Duch, J. Kacprzyk, E. Oja, et al., pp. 153-160, Springer-Verlag Berlin Heidelberg.
  • Muresan R.C. (2004), Scale Independence in the Visual System, in: "Rajapakse, Jagath C.; Wang, Lipo (Eds). Neural Information, Processing: Research and Development", Springer-Verlag, pp. 1-18.
  • Muresan R.C. and Ignat I. (2004), Principles of Design for Large Scale Neural Simulators. Proceedings of the International Conference on Automation, Quality and Testing, Robotics 2004.
  • Muresan R.C. and Ignat I. (2004), The "Neocortex" Neural Simulator. A Modern Design. Proceedings of the International Conference on Intelligent Engineering Systems 2004.
  • Muresan R.C. (2004), The Coherence Theory: Simple Attentional Modulation Effects. Neurocomputing, Vol. 58-60C, Special Issue: Computational Neuroscience: Trends in Research 2004 Edited by E. De Schutter, pp. 949-955, 2004.
  • Muresan R.C. (2003), Pattern Recognition Using Pulse-Coupled Neural Networks and Discrete Fourier Transforms. Neurocomputing, vol. 51C, pp. 487-493.
  • Muresan R.C. (2003), RetinotopicNET: An Efficient Simulator for Retinotopic Visual Architectures. Proceedings of the European Symposium on Artificial Neural Networks, Bruges, April 23-25 2003, pp. 247-254.
  • Muresan R.C. (2002), Visual Scale Independence in a Network of Spiking Neurons. Proceedings of 9th International Conference on Neural Information Processing Proceedings (ICONIP), Singapore, Vol. 4, pp. 1739-1743.
  • Muresan R.C. (2002), Complex Object Recognition Using a Biologically Plausible Neural Model, In: Advances in Simulation, Systems Theory and Systems Engineering, WSEAS Press: Athens, pp. 163-168.
  • Dan F. and Muresan R.C. (2006), Semaphorized intersections. Polution and Optimization, Mediamira 2006.