Personal Website

Kerstin Lenk, Ass. Prof. Dr. rer. nat.
Institute of Neural Engineering
Graz University of Technology
Stremayrgasse 16/IV
8010 Graz, Austria
Tel: +43-316-873-30712

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June 2022: I present a poster at the FENS Forum in Paris.
September 2021: I give a talk at the ÖGBMT in Graz.
September 2021: I give a talk at the 8th ACM Nanocom (online)
July 2021: I present a poster at the XV European Meeting on Glial Cells in Health and Disease (online).
April 2021: I become Assistant Professor.
March 2021: I start at the INE.

Short Bio

Since April 2021, I am an Assistant Professor at the Institute of Neural Engineering. I studied Computer Science with a major in medical informatics at Lausitz University of Applied Sciences in Senftenberg, Germany. I wrote my diploma thesis with the title "Use of image processing techniques for dyssynchrony analysis on MR ventricular volumetric data in Tetralogy of Fallot" (motion analysis of the right ventricle of the heart in 3D space) at King's College London, UK.
During my Ph.D., I developed a neuronal network model that simulates the activity of up to 10,000 neurons. One focus was to model the influence of neuroactive substances, for example, antiepileptic drugs, on the neuronal synapses and thus to be able to draw conclusions about the connections between neurons in the network. In 2016, I received my Ph.D. (Dr. rer. nat.) in Computer Science at Clausthal University of Technology, Germany.

In December 2016, I started my first Postdoctoral position at the TU Dresden, Germany. There, I analyzed transcriptomic data of human stem cell-derived neurons with bioinformatics tools. In 2018, I was granted a prestigious position as a Postdoctoral Researcher by the Academy of Finland. At Tampere University (TUNI, former TUT) in Finland, I started to develop computational models of local calcium dynamics in human single-cell astrocytes and neuron-astrocyte networks.

My Publications

My publications can be found on:
Google Scholar


Verfassen wissenschaftlicher Arbeiten
Selected Topics of Neural Engineering


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