Tobias Neckel

736 total citations
32 papers, 380 citations indexed

About

Tobias Neckel is a scholar working on Computational Mechanics, Artificial Intelligence and Statistics, Probability and Uncertainty. According to data from OpenAlex, Tobias Neckel has authored 32 papers receiving a total of 380 indexed citations (citations by other indexed papers that have themselves been cited), including 11 papers in Computational Mechanics, 5 papers in Artificial Intelligence and 5 papers in Statistics, Probability and Uncertainty. Recurrent topics in Tobias Neckel's work include Lattice Boltzmann Simulation Studies (8 papers), Probabilistic and Robust Engineering Design (5 papers) and Computational Fluid Dynamics and Aerodynamics (5 papers). Tobias Neckel is often cited by papers focused on Lattice Boltzmann Simulation Studies (8 papers), Probabilistic and Robust Engineering Design (5 papers) and Computational Fluid Dynamics and Aerodynamics (5 papers). Tobias Neckel collaborates with scholars based in Germany, United States and Oman. Tobias Neckel's co-authors include Hans‐Joachim Bungartz, Miriam Mehl, Philipp Neumann, Tobias Weinzierl, F. Jenko, Gerta Köster, Andrew Philippides, Anne Templeton, John Drury and Bernhard Gatzhammer and has published in prestigious journals such as Journal of Computational Physics, Computer Methods in Applied Mechanics and Engineering and Computer Physics Communications.

In The Last Decade

Tobias Neckel

30 papers receiving 367 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Tobias Neckel Germany 12 105 76 57 51 47 32 380
Dirk Pflüger Germany 13 87 0.8× 37 0.5× 35 0.6× 32 0.6× 43 0.9× 71 470
V. Akçelik United States 8 66 0.6× 61 0.8× 167 2.9× 41 0.8× 50 1.1× 12 595
E.M. Oblow United States 14 44 0.4× 99 1.3× 25 0.4× 51 1.0× 31 0.7× 51 538
Guofei Pang China 12 117 1.1× 47 0.6× 18 0.3× 219 4.3× 48 1.0× 25 738
P. Khademi United States 4 100 1.0× 39 0.5× 20 0.4× 23 0.5× 17 0.4× 4 343
Curtis Ober United States 9 307 2.9× 16 0.2× 186 3.3× 36 0.7× 50 1.1× 31 687
René Pinnau Germany 17 424 4.0× 41 0.5× 21 0.4× 99 1.9× 98 2.1× 77 861
Harvey Dubner United States 8 45 0.4× 31 0.4× 29 0.5× 40 0.8× 49 1.0× 22 573
Claudia Schillings Germany 15 93 0.9× 253 3.3× 55 1.0× 67 1.3× 14 0.3× 30 495
Shuai Lu China 15 153 1.5× 32 0.4× 33 0.6× 10 0.2× 42 0.9× 58 705

Countries citing papers authored by Tobias Neckel

Since Specialization
Citations

This map shows the geographic impact of Tobias Neckel's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Tobias Neckel with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Tobias Neckel more than expected).

Fields of papers citing papers by Tobias Neckel

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Tobias Neckel. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Tobias Neckel. The network helps show where Tobias Neckel may publish in the future.

Co-authorship network of co-authors of Tobias Neckel

This figure shows the co-authorship network connecting the top 25 collaborators of Tobias Neckel. A scholar is included among the top collaborators of Tobias Neckel based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Tobias Neckel. Tobias Neckel is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Dietrich, Felix, et al.. (2024). Multi-fidelity Gaussian process surrogate modeling for regression problems in physics. Machine Learning Science and Technology. 5(4). 45015–45015. 8 indexed citations
2.
Peherstorfer, Benjamin, et al.. (2023). Context-aware learning of hierarchies of low-fidelity models for multi-fidelity uncertainty quantification. Computer Methods in Applied Mechanics and Engineering. 406. 115908–115908. 12 indexed citations
3.
Latz, Jonas, et al.. (2020). Multilevel Adaptive Sparse Leja Approximations for Bayesian Inverse Problems. SIAM Journal on Scientific Computing. 42(1). A424–A451. 6 indexed citations
4.
Neckel, Tobias, et al.. (2019). Prediction and reduction of runtime in non-intrusive forward UQ simulations. SN Applied Sciences. 1(9). 2 indexed citations
5.
Uekérmann, Benjamin, et al.. (2018). Nonintrusive Uncertainty Analysis of Fluid-Structure Interaction with Spatially Adaptive Sparse Grids and Polynomial Chaos Expansion. SIAM Journal on Scientific Computing. 40(2). B457–B482. 4 indexed citations
6.
Dietrich, Felix, et al.. (2018). FAST AND FLEXIBLE UNCERTAINTY QUANTIFICATION THROUGH A DATA-DRIVEN SURROGATE MODEL. International Journal for Uncertainty Quantification. 8(2). 175–192. 7 indexed citations
7.
Bungartz, Hans‐Joachim, et al.. (2017). Block-structured grids in full velocity space for Eulerian gyrokinetic simulations. Computer Physics Communications. 215. 49–62. 10 indexed citations
8.
Neckel, Tobias, et al.. (2014). GPU Optimization of Pseudo Random Number Generators for Random Ordinary Differential Equations. Procedia Computer Science. 29. 172–183. 5 indexed citations
9.
Schreiber, Martin, et al.. (2014). Invasive Compute Balancing for Applications with Shared and Hybrid Parallelization. International Journal of Parallel Programming. 43(6). 1004–1027. 5 indexed citations
10.
Neckel, Tobias, et al.. (2013). . DIAL (Catholic University of Leuven). 58 indexed citations
11.
Neckel, Tobias, et al.. (2013). Random Differential Equations in Scientific Computing. Directory of Open access Books (OAPEN Foundation). 16 indexed citations
12.
Schreiber, Martin, et al.. (2013). Invasive Compute Balancing for Applications with Hybrid Parallelization. 136–143.
13.
Neckel, Tobias, et al.. (2012). Towards a Navier Stokes-Darcy Upscaling Based on Permeability Tensor Computation. Procedia Computer Science. 9. 717–726. 2 indexed citations
14.
Neumann, Philipp, Hans‐Joachim Bungartz, Miriam Mehl, Tobias Neckel, & Tobias Weinzierl. (2012). A Coupled Approach for Fluid Dynamic Problems Using the PDE Framework Peano. Communications in Computational Physics. 12(1). 65–84. 8 indexed citations
15.
Gatzhammer, Bernhard, Miriam Mehl, & Tobias Neckel. (2010). A coupling environment for partitioned multiphysics simulations applied to fluid-structure interaction scenarios. Procedia Computer Science. 1(1). 681–689. 15 indexed citations
16.
Bäder, Michael, et al.. (2009). Software engineering meets scientific computing: group projects in CSE education. International Journal of Computational Science and Engineering. 4(4). 245–253.
17.
Bungartz, Hans‐Joachim, Miriam Mehl, Tobias Neckel, & Tobias Weinzierl. (2009). The PDE framework Peano applied to fluid dynamics: an efficient implementation of a parallel multiscale fluid dynamics solver on octree-like adaptive Cartesian grids. Computational Mechanics. 46(1). 103–114. 36 indexed citations
18.
Mehl, Miriam, et al.. (2008). An Eulerian approach for partitioned fluid–structure simulations on Cartesian grids. Computational Mechanics. 43(1). 115–124. 10 indexed citations
19.
Bungartz, Hans‐Joachim, et al.. (2006). CARTESIAN DISCRETISATIONS FOR FLUID-STRUCTURE INTERACTION { CONSISTENT FORCES. Research Repository (Delft University of Technology). 2 indexed citations
20.
Neckel, Tobias, et al.. (2003). Collocation and inversion for a reentry optimal control problem. mediaTUM (Technical University of Munich). 15 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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