Kai Bergermann
Member of the Research Group
Scientific Computing
Phone:
+49 371 531 37610
Fax:
+49 371 531 22509
Office:
Reichenhainer Str. 41, Zimmer 612
ORCID:
Scholar:
Github:
Researchgate
- February-April 2023, research stay with Prof. Francesco Tudisco at Gran Sasso Science Institute, L'Aquila, Italy
- Since January 2021, member of the research group Scientific Computing (Prof. Dr. Martin Stoll), TU Chemnitz, Germany
- February-December 2020, member of the research group Numerical Mathematics (Partial Differential Equations) (Prof. Dr. Roland Herzog), TU Chemnitz, Germany
- January 2020, M.Sc. in Industrial Mathematics
- 2017-2020, Study of Industrial Mathematics at TU Chemnitz, Germany
- February 2015, B.Sc. in Mathematics
- 2011-2015, Study of Mathematics at University of Freiburg, Germany
Submitted articles
- K. Bergermann, M. Stoll, and F. Tudisco
A nonlinear spectral core-periphery detection method for multiplex networks, 2023
arXiv:2310.19697
Code available here
Journal articles
- K. Bergermann and M. Stoll
Adaptive rational Krylov methods for exponential Runge--Kutta integrators
SIAM Journal on Matrix Analysis and Applications, 45(1), p.744-770, 2024
DOI: 10.1137/23M1559439
arXiv:2303.09482
Code available here
- K. Bergermann and M. Wolter
A Twitter network and discourse analysis of the Rana Plaza collapse
Applied Network Science, 8, 74, 2023
DOI: 10.1007/s41109-023-00587-y
arXiv:2304.14706
Code available here
- K. Bergermann, C. Deibel, R. Herzog, R. C. I. MacKenzie, J.-F. Pietschmann, and M. Stoll
Preconditioning for a phase-field model with application to morphology evolution in organic semiconductors
Communications in Computational Physics, 34(1), p.1-17, 2023
DOI: 10.4208/cicp.OA-2022-0115
arXiv:2204.03575
Code available here
- K. Bergermann and M. Stoll
Fast computation of matrix function-based centrality measures for layer-coupled multiplex networks
Physical Review E, 105(3), 034305, 2022
DOI: 10.1103/PhysRevE.105.034305
arXiv:2104.14368
Code available here
- K. Bergermann and M. Stoll
Orientations and matrix function-based centralities in multiplex network analysis of urban public transport
Applied Network Science, 6, 90, 2021
DOI: 10.1007/s41109-021-00429-9
Code available here
Data available here
- K. Bergermann, M. Stoll, and T. Volkmer
Semi-supervised learning for aggregated multilayer graphs using diffuse interface methods and fast matrix vector products
SIAM Journal on Mathematics of Data Science, 3(2), p.758-785, 2021
DOI: 10.1137/20M1352028
arXiv:2007.05239
Code available here
- F. Ospald, K. Bergermann, and R. Herzog
An extension of the strain transfer principle for fiber reinforced materials
Computational Mechanics, 67(5), p.1453-1463, 2021
DOI: 10.1007/s00466-021-01997-4
Code available here
- K. Bergermann
Modeling the morphology evolution of organic solar cells
GAMM Archive for Students, 1(1), p.18-27, 2019
DOI: 10.14464/GAMMAS.V1I1.419
Code available here
Other articles
- M. Stoll and K. Bergermann
Multilayer networks and their applications
GAMM Rundbrief, 2/2022, p.4-9
Summer term 2024
Winter term 2023/24
Summer term 2023
Winter term 2022/23
Summer term 2022
Winter term 2021/22
Summer term 2021
Winter term 2020/21
- Exercise Introduction to Data Science (second half)