My name is Daniel Müller-Komorowska and I am a data scientist. I started out as a neuroscientist, recording and analyzing electrical signals from neurons. I used Python with NumPy, SciPy and Pandas to analyze these neuronal time-series data. I used Matplotlib and Seaborn for data visualization. I also used dimensionality reduction and clustering with scikit-learn, scanpy and R on single cell sequencing data. Finally, I have simulated spiking neuronal networks with NEURON and artifical neural networks with PyTorch.

For recent projects I have used MATLAB for electrical circuit simulations. I also started learning Julia, where I have focused on simulating neural systems. On this website I run my Scientific Programming blog, where I write about programming and data science topics.


Müller-Komorowska, D., Opitz, T., Elzoheiry, S., Schweizer, M., Ambrad Giovannetti, E., & Beck, H. (2020). Nonspecific Expression in Limited Excitatory Cell Populations in Interneuron-Targeting Cre-driver Lines Can Have Large Functional Effects. Frontiers in Neural Circuits, 14(April), 1–13. https://doi.org/10.3389/fncir.2020.00016

Braganza, O., Müller-Komorowska, D., Kelly, T., & Beck, H. (2020). Quantitative properties of a feedback circuit predict frequency-dependent pattern separation. ELife, 813188. https://doi.org/10.7554/eLife.53148

Schmidt, S., Pothmann, L., Müller-Komorowska, D., Opitz, T., da Silva, P. S., Beck, H. (2021). Complex effects of eslicarbazepine on inhibitory micronetworks in chronic experimental epilepsy. Epilepsia. https://doi.org/10.1111/epi.16808

Müller-Komorowska, D., Parabucki, A., Elyasaf, G., Katz, Y., Beck, H., & Lampl, I. (2021). A novel theoretical framework for simultaneous measurement of excitatory and inhibitory conductances. 17(12), e1009725. https://doi.org/10.1371/journal.pcbi.1009725