Carl Shneider

Full Name

Dr. C. Shneider

Email

Carl.Shneider@cwi.nl

Phone

+31 20 592 4208

Room

M136

Department(s)

Multiscale Dynamics

Function(s)

Researcher

Carl Shneider

Muñoz-Jaramillo, A., Jungbluth, A., Gitiaux, X., Wright, P.J. (Paul J.), Shneider, C., Maloney, S., … Kalaitzis, F. (Freddie). (2024). Physically motivated deep learning to superresolve and cross calibrate solar magnetograms. The Astrophysical Journal Supplement Series, 271(2), 46:1–46:18. doi:10.3847/1538-4365/ad12c2
Poduval, B., McPherron, R. L., Walker, R., Himes, M. D., Pitman, K. M., Azari, A. R., … Wing, S. (2023). AI-ready data in space science and solar physics: problems, mitigation and action plan. Frontiers in Astronomy and Space Sciences, 10. doi:10.3389/fspas.2023.1203598
Hu, A., Shneider, C., Tiwari, A., & Camporeale, E. (2022). Probabilistic prediction of Dst storms one-day-ahead using full-disk SoHO images. Space Weather, 20(8), e2022SW003064:1–e2022SW003064:17. doi:10.1029/2022SW003064
Hatfield, P., Gaffney, J., Anderson, G., Ali, S., Antonelli, L., Başeğmez du Pree, S., … Williams, B. (2021). The data-driven future of high-energy-density physics. Nature, 593(7859), 351–361. doi:10.1038/s41586-021-03382-w
Kuzniar, A., Maassen, J., Verhoeven, S., Santuari, L., Shneider, C., Kloosterman, W., & de Ridder, J. (2018). A portable and scalable workflow for detecting structural variants in whole-genome sequencing data. In Proceedings of the International Conference on e-Science and Grid Computing (pp. 303–304). doi:10.1109/eScience.2018.00064
The Computational Pan-Genomics Consortium, Marschall, T., Marz, M., Abeel, T., Dijkstra, L., Dutilh, B., … Schönhuth, A. (2018). Computational pan-genomics: status, promises and challenges. Briefings in Bioinformatics, 19(1), 118–135. doi:10.1093/bib/bbw089

Member: NASA Ames and SETI Institute sponsored 8 week Frontier Development Lab (FDL) program
Member: The Super-Resolution of Solar Magnetograms Team
Member: American Geophysical Union (AGU)