He earned a Master’s degree in Informatics from the University of Ghent, focusing his thesis on building a Turing machine in a pulsed neural network computer.
As a researcher in Computational Neuroscience at the University of Antwerp, Werner studied Cerebellar Purkinje Neurons. He also developed software for automating the parameter optimization of neuronal models.
His career next took him to the Okinawa Institute of Science and Technology in Japan. Over three and a half years, he not only continued his research but also played a role in maintaining the High-Performance Computing infrastructure.
In 2011, Werner moved to Switzerland to contribute to the Blue Brain Project at the EPFL in Lausanne. There, his roles evolved from researcher and engineer in the single neuron model building pipeline to the group leader. In this position, he oversaw the creation and curation of electrical neuron models and morphologies, as well as the development and maintenance of relevant software.
In 2023, Werner joined the IT’IS Foundation as a Project Leader. His focus is now on helping the development of a metamodeling framework for o2S2PARC.
| Arnaudon, A., Reva, M., Zbili, M., Markram, H., Van Geit, W. & Kanari, L. Controlling morpho-electrophysiological variability of neurons with detailed biophysical models. iScience, Elsevier, 2023, doi:10.1016/j.isci.2023.108222 |
| Iavarone, E., Simko, J., Shi, Y., Bertschy, M., García-Amado, M., Litvak, P., Kaufmann, A.K., O'Reilly, C., Amsalem, O., Abdellah, M., Chevtchenko, G., Coste, B., Courcol, J.D., Ecker, A., Favreau, C., Fleury, A.C., Van Geit, W., Gevaert, M., Guerrero, N.R., Herttuainen, J., Ivaska, G., Kerrien, S., King, J.G., Kumbhar, P., Lurie, P., Magkanaris, I., Muddapu, V.R., Nair, J., Pereira, F.L., Perin, R., Petitjean, F., Ranjan, R., Reimann, M., Soltuzu, L., Sy, M.F.c., Tuncel, M.A., Ulbrich, A., Wolf, M., Clascá, F., Markram, H. & Hill, S.L. Thalamic control of sensory processing and spindles in a biophysical somatosensory thalamoreticular circuit model of wakefulness and sleep. Cell Reports, 42(3):112200, 2023, doi:10.1016/j.celrep.2023.112200 |
| Reva, M., Rössert, C., Arnaudon, A., Damart, T., Mandge, D., Tuncel, A., Ramaswamy, S., Markram, H. & Van Geit, W. A universal workflow for creation, validation, and generalization of detailed neuronal models. Patterns, 4(11):100855, 2023, doi:10.1016/j.patter.2023.100855 |
| Wei, Y., Nandi, A., Jia, X., Siegle, J.H., Denman, D., Lee, S.Y., Buchin, A., Van Geit, W., Mosher, C.P., Olsen, S. & Anastassiou, C.A. Associations between in vitro, in vivo and in silico cell classes in mouse primary visual cortex. Nature Communications, 14(1):2344, 2023, doi:10.1038/s41467-023-37844-8 |
| Weise, K., Worbs, T., Kalloch, B., Souza, V.H., Jaquier, A.T., Van Geit, W., Thielscher, A. & Knösche, T.R. Directional sensitivity of cortical neurons towards TMS induced electric fields. Imaging Neuroscience, 2023, doi:10.1162/imag_a_00036 |
| Chindemi, G., Abdellah, M., Amsalem, O., Benavides-Piccione, R., Delattre, V., Doron, M., Ecker, A., Jaquier, A.T., King, J., Kumbhar, P., Monney, C., Perin, R., Rössert, C., Tuncel, A.M., Van Geit, W., DeFelipe, J., Graupner, M., Segev, I., Markram, H. & Muller, E.B. A calcium-based plasticity model for predicting long-term potentiation and depression in the neocortex. Nature Communications, 13(1):3038, 2022, doi:10.1038/s41467-022-30214-w |
| Kanari, L., Dictus, H., Chalimourda, A., Arnaudon, A., Van Geit, W., Coste, B., Shillcock, J., Hess, K. & Markram, H. Computational synthesis of cortical dendritic morphologies. Cell Reports, 39(1):110586, 2022, doi:10.1016/j.celrep.2022.110586 |
| Nandi, A., Chartrand, T., Van Geit, W., Buchin, A., Yao, Z., Lee, S.Y., Wei, Y., Kalmbach, B., Lee, B., Lein, E., Berg, J., Sümbül, U., Koch, C., Tasic, B. & Anastassiou, C.A. Single-neuron models linking electrophysiology, morphology, and transcriptomics across cortical cell types. Cell Reports, 40(6):111176, 2022, doi:10.1016/j.celrep.2022.111176 |
| Shapira, G., Marcus-Kalish, M., Amsalem, O., Van Geit, W., Segev, I. & Steinberg, D.M. Statistical emulation of neural simulators: Application to neocortical L2/3 large basket cells. Frontiers in Big Data, 5:789962, 2022, doi:10.3389/fdata.2022.789962 |
| Sáray, S., Rössert, C.A., Appukuttan, S., Migliore, R., Vitale, P., Lupascu, C.A., Bologna, L.L., Van Geit, W., Romani, A., Davison, A.P., Muller, E., Freund, T.F. & Káli, S. HippoUnit: A software tool for the automated testing and systematic comparison of detailed models of hippocampal neurons based on electrophysiological data. PLOS Computational Biology, 17(1):e1008114, Lytton, W.W.(eds), 2021, doi:10.1371/journal.pcbi.1008114 |
| Iavarone, E., Yi, J., Shi, Y., Zandt, B.J., O'Reilly, C., Van Geit, W., Rössert, C., Markram, H. & Hill, S.L. Experimentally-constrained biophysical models of tonic and burst firing modes in thalamocortical neurons. PLOS Computational Biology, 15(5):e1006753, Lytton, W.W.(eds), 2019, doi:10.1371/journal.pcbi.1006753 |
| Migliore, R., Lupascu, C.A., Bologna, L.L., Romani, A., Courcol, J.D., Antonel, S., Van Geit, W.A., Thomson, A.M., Mercer, A., Lange, S. & thers, . The physiological variability of channel density in hippocampal CA1 pyramidal cells and interneurons explored using a unified data-driven modeling workflow. PLoS computational biology, 14(9):e1006423, Public Library of Science San Francisco, CA USA, 2018, doi:10.1371/journal.pcbi.1006423 |
| Masoli, S., Rizza, M.F., Sgritta, M., Van Geit, W., Schürmann, F. & D'Angelo, E. Single neuron optimization as a basis for accurate biophysical modeling: The case of cerebellar granule cells. Frontiers in Cellular Neuroscience, 11, 2017, doi:10.3389/fncel.2017.00071 |
| Amsalem, O., Van Geit, W., Muller, E., Markram, H. & Segev, I. From neuron biophysics to orientation selectivity in electrically coupled networks of neocortical L2/3 large basket cells. Cerebral Cortex, 26(8):3655-3668, Oxford University Press, 2016, doi:10.1093/cercor/bhw166 |
| Van Geit, W., Gevaert, M., Chindemi, G., Rössert, C., Courcol, J.D., Muller, E.B., Schürmann, F., Segev, I. & Markram, H. BluePyOpt: Leveraging open source software and cloud infrastructure to optimise model parameters in neuroscience. Frontiers in Neuroinformatics, 10(17), 2016, doi:10.3389/fninf.2016.00017 |
| Markram, H., Muller, E., Ramaswamy, S., Reimann, M.W., Abdellah, M., Sanchez, C. .A., Ailamaki, A., Alonso-Nanclares, L., Antille, N., Arsever, S., Kahou, G.A. .A., Berger, T.K., Bilgili, A., Buncic, N., Chalimourda, A., Chindemi, G., Courcol, J.D., Delalondre, F., Delattre, V., Druckmann, S., Dumusc, R., Dynes, J., Eilemann, S., Gal, E., Gevaert, M.E., Ghobril, J.P., Gidon, A., Graham, J.W., Gupta, A., Haenel, V., Hay, E., Heinis, T., Hernando, J.B., Hines, M., Kanari, L., Keller, D., Kenyon, J., Khazen, G., Kim, Y., King, J.G., Kisvarday, Z., Kumbhar, P., Lasserre, S., Le Bé, J.V., Magalh\~aes, B.R.C., Merchán-Pérez, A., Meystre, J., Morrice, B.R., Muller, J., Mu\~noz-Céspedes, A., Muralidhar, S., Muthurasa, K., Nachbaur, D., Newton, T.H., Nolte, M., Ovcharenko, A., Palacios, J., Pastor, L., Perin, R., Ranjan, R., Riachi, I., Rodr\'\iguez, J.R., Riquelme, J.L., Rössert, C., Sfyrakis, K., Shi, Y., Shillcock, J.C., Silberberg, G., Silva, R., Tauheed, F., Telefont, M., Toledo-Rodriguez, M., Tränkler, T., Van Geit, W., D\'\iaz, J.V., Walker, R., Wang, Y., Zaninetta, S.M., DeFelipe, J., Hill, S.L., Segev, I. & Schürmann, F. Reconstruction and simulation of neocortical microcircuitry. Cell, 163(2):456-492, 2015, doi:10.1016/j.cell.2015.09.029 |
| Van Geit, W., De Schutter, E. & Achard, P. Automated neuron model optimization techniques: A review. Biological Cybernetics, 99(4-5):241-251, 2008, doi:10.1007/s00422-008-0257-6 |
| Van Geit, W., Achard, P. & De Schutter, E. Neurofitter: A parameter tuning package for a wide range of electrophysiological neuron models. Frontiers in Neuroinformatics, 1:89, Frontiers, 2007, doi:10.3389/neuro.11.001.2007 |
| Isbister, J.B., Ecker, A., Pokorny, C., Bola\~nos-Puchet, S., Egas Santander, D., Arnaudon, A., Awile, O., Barros-Zulaica, N., Blanco Alonso, J., Boci, E., Chindemi, G., Courcol, J.D., Damart, T., Delemontex, T., Dietz, A., Ficarelli, G., Gevaert, M., Herttuainen, J., Ivaska, G., Ji, W., Keller, D., King, J., Kumbhar, P., Lapere, S., Litvak, P., Mandge, D., Muller, E.B., Pereira, F., Planas, J., Ranjan, R., Reva, M., Romani, A., Rössert, C., Schürmann, F., Sood, V., Teska, A., Tuncel, A., Van Geit, W., Wolf, M., Markram, H., Ramaswamy, S. & Reimann, M.W. Modeling and simulation of neocortical micro- and mesocircuitry. Part II: Physiology and experimentation. bioRxiv, 2023, doi:10.1101/2023.05.17.541168 |
| Buccino, A.P., Damart, T., Bartram, J., Mandge, D., Xue, X., Zbili, M., Gänswein, T., Jaquier, A., Emmenegger, V., Markram, H., Hierlemann, A. & Van Geit, W. A Multi-Modal Fitting Approach to Construct Single-Neuron Models with Patch Clamp and High-Density Microelectrode Arrays. bioRxiv, 2022, doi:10.1101/2022.08.03.502468 |
| Damart, T.P.L., Jaquier, A., Arnaudon, A., Mandge, D., Van Geit, W. & Kilic, I. BluePyEModel. , Zenodo, 2023, doi:10.5281/zenodo.8283490 |
| Jaquier, A., Tuncel, A. & Van Geit, W. EModelRunner. , Zenodo, 2023, doi:10.5281/zenodo.8116075 |
| Jaquier, A., Tuncel, A., Van Geit, W., Alonso, L.M. & Marder, E. Currentscape. , Zenodo, 2023, doi:10.5281/zenodo.8046373 |
| Ranjan, R., Van Geit, W., Moor, R., Rössert, C., Riquelme, J.L., Damart, T., Jaquier, A. & Tuncel, A. eFEL. , Zenodo, 2023, doi:10.5281/zenodo.593869 |
| Van Geit, W., Gevaert, M., Damart, T., Rössert, C., Courcol, J.D., Chindemi, G., Jaquier, A. & Muller, E. BluePyOpt. , Zenodo, 2023, doi:10.5281/zenodo.8135890 |
| Van Geit, W., Tuncel, A., Gevaert, M., Torben-Nielsen, B. & Muller, E. BlueCelluLab. , Zenodo, 2023, doi:10.5281/zenodo.8113483 |
| Van Geit, W., Vanherpe, L., Rössert, C., Gevaert, M., Courcol, J.D., King, J.G. & Jaquier, A. BluePyMM. , Zenodo, 2023, doi:10.5281/zenodo.8146238 |
| Van Geit, W., Achard, P. & De Schutter, E. Neurofitter. , 2007 |
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https://orcid.org/0000-0002-2915-720X
