Marwan Abdellah


Computing
Scientific Visualization
Marwan Abdellah is a Scientific Visualization Engineer and Post Doctoral Fellow in the Scientific Visualization Section of the Computing Division.

His current research focuses on building accurate computational models of brain imaging technologies using physically plausible methods.

Marwan joined the Blue Brain in 2011 as a Software Engineer and led the multimedia generation workflows, and also contributed to the development of the software applications required for the interactive visualisation of the neocortical digital models. His research interests include scientific visualisation, physically-plausible rendering, computer graphics and modelling, medical imaging, high performance computing and in silico neuroscience.

Marwan obtained his PhD in Neuroscience from EPFL in 2017. He gained his Bachelor and Master’s degrees from the Biomedical Engineering Department, School of Engineering at Cairo University, Egypt.

Selected Publications

Abdellah, M., Cantero, J. J. G., Guerrero, N. R., Foni, A., Coggan, J. S., Calì, C., … & Schürmann, F. (2022). Ultraliser: a framework for creating multiscale, high-fidelity and geometrically realistic 3D models for in silico neuroscience. bioRxiv. https://www.biorxiv.org/content/10.1101/2022.07.27.501675v1.abstract

Newton, T. H., Reimann, M. W., Abdellah, M., Chevtchenko, G., Muller, E. B., & Markram, H. (2021). In silico voltage-sensitive dye imaging reveals the emergent dynamics of cortical populations. Nature communications, 12(1), 1-13 https://www.nature.com/articles/s41467-021-23901-7

Chindemi, G., Abdellah, M., Amsalem, O., Benavides-Piccione, R., Delattre, V., Doron, M., … & Muller, E. B. (2022). A calcium-based plasticity model for predicting long-term potentiation and depression in the neocortex. Nature Communications, 13(1), 1-19. https://www.nature.com/articles/s41467-022-30214-w

Abdellah, M., Foni, A., Zisis, E., Guerrero, N. R., Lapere, S., Coggan, J. S., … & Schürmann, F. (2021). Metaball skinning of synthetic astroglial morphologies into realistic mesh models for in silico simulations and visual analytics. Bioinformatics, 37(Supplement_1), i426-i433. https://academic.oup.com/bioinformatics/article-abstract/37/Supplement_1/i426/6319688

Abdellah, M., Hernando, J., Eilemann, S., Lapere, S., Antille, N., Markram, H., & Schürmann, F. (2018). NeuroMorphoVis: a collaborative framework for analysis and visualization of neuronal morphology skeletons reconstructed from microscopy stacks. Bioinformatics, 34(13), i574-i582. https://academic.oup.com/bioinformatics/article/34/13/i574/5045775?login=true

Abdellah, M., Guerrero, N. R., Lapere, S., Coggan, J. S., Keller, D., Coste, B., … & Schürmann, F. (2020). Interactive visualization and analysis of morphological skeletons of brain vasculature networks with VessMorphoVis. Bioinformatics, 36(Supplement_1), i534-i541. https://academic.oup.com/bioinformatics/article/36/Supplement_1/i534/5870503

Markram, H., Muller, E., Ramaswamy, S., Reimann, M. W., Abdellah, M., Sanchez, C. A., … & Schürmann, F. (2015). Reconstruction and simulation of neocortical microcircuitry. Cell, 163(2), 456-492. https://www.sciencedirect.com/science/article/pii/S0092867415011915