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Sreedhar Saseendran Kumar

PhD Student


    Sreedhar Saseendran Kumar
    Dept. for Microsystems Engineering, IMTEK
    Georges-Koehler-Allee 102
    D-79110 Freiburg, Germany i. Br.
    Tel .: +49 (0) 761 203 67744
    Fax: +49 (0) 761 203 97759


Research Project

Research Topics

  •  Autonomous control of network activity



  • Dissociated cortical cultures
  • Microelectrode array (MEA) recordings
  • Machine learning



Academic Background

  • Since 10/2012: PhD student at the Department of Microsystems Technology (IMTEK) and Bernstein Center Freiburg (NAMASEN Marie Curie ITN).
  • 08 / 2010-09 / 2012: M.Sc. "Mathematical Modeling in Engineering" (Erasmus Mundus Masterscourse), University of L'Aquila, Italy, and University of Hamburg, Germany
  • 08 / 2004-04 / 2008: B.Sc. "Technical, Electrical and Electronics Engineering", National Institute of Technology, Karnataka, India

Teaching Experiences

  • 06 / 2008-06 / 2010: Lecturer at Rajagiri School of Engineering and Technology, Mahathma Gandhi University, Kerala, India
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  • Kumar SS, Wülfing J, Okujeni S, Boedecker J, Riedmiller M, Egert U (2016) Autonomous optimization of targeted stimulation of neural networks. PloS Comput Biol 12 (8): e1005054, doi: 10.1371 / journal.pcbi.1005054.
  • Palumbo P, Pepe P, Kong J D, Kumar S S, Panunzi S and De Gaetano A (2013) Regulation of the human plasma glycemia by means of glucose measurements and subcutaneous insulin administration, 3 rd IFAC International Conference on Intelligent Control and Automation Science, Chengdu, China, pp. 519 – 524.
  • Tessadori J, Venuta D, Kumar SS, Bisio M, Pasquale V and Chiappalone, Embodied Neural Assemblies: A closed loop environment for coding and decoding studies, 6th International IEEE / EMBS Conference on Neural Engineering (NER), 2013, pages 899-902 FIG.
  • Tessadori J, Venuta D, Pasquale V, Kumar SS and Chiappalone M, encoding of stimuli in embodied neuronal networks, Lepora N, Mura A, madder HG, Verschure P, and Prescott TJ, editors, Biomimetic and Biohybrid Systems, volume 8064 of Lecture Notes in Computer Science, pages 274-286. Springer Berlin-Heidelberg, 2013.
  • JD Kong, SS Kumar, P. Palumbo (2014), DDE models of the glucose insulin system: a useful tool for the artificial pancreas, in: Managing Complexity, Reducing Perplexity in Biological Systems, M. Delitala, G. Ajomne-Marsan Editors ), Springer Proceedings in Mathematics & Statistics, Vol. 67, pp. 109-117, doi: 10.1007 / 978-3-319-03759-2_12.


Conference Abstracts

  • Kumar SS, Wülfing J, Okujeni S, Boedecker J, Riedmiller M and Egert U (2016), A machine learning based approach to control network activity. Front. Neurosci. Conference Abstract: MEA Meeting 2016, 10th International Meeting on Substrate Integrated Electrode Arrays, doi: 10.3389 / conf.fnins.2016.93.00117.
  • Kumar SS, Wülfing J, Okujeni S, Boedecker J, Riedmiller M and Egert U (2016), Autonomous Control of Network Activity, JS Pezaris, NG Hatsopoulos (eds.) Proceedings of AREADNE 2016, Santorini, Greece, 22-26 June 2016 , published by The AREADNE Foundation, Inc., Cambridge, Massachusetts, ( Link )
  • Kumar SS, Wülfing J, Winterer L, Okujeni S, Boedecker J, Wimmer R, Riedmiller M, Becker B, Egert U (2015) Autonomous Control of Network Activity. Bernstein Conference 2015, doi: 10.12751 / nncn.bc2015.0041. 
  • S. Kumar, J. Wülfing, R. Wimmer, S. Okujeni, J. Boedecker, M. Riedmiller, B. Becker, U. Egert, Autonomous Control of Network Activity, Proc. of the 9th International Meeting on Substrate-Integrated Microelectrode Arrays, Reutlingen (Editors: Alfred Stett, Günther Zeck); July 1-4, 2014.


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