Susan M. Mniszewski

1.9k total citations
49 papers, 870 citations indexed

About

Susan M. Mniszewski is a scholar working on Artificial Intelligence, Atomic and Molecular Physics, and Optics and Hardware and Architecture. According to data from OpenAlex, Susan M. Mniszewski has authored 49 papers receiving a total of 870 indexed citations (citations by other indexed papers that have themselves been cited), including 21 papers in Artificial Intelligence, 14 papers in Atomic and Molecular Physics, and Optics and 7 papers in Hardware and Architecture. Recurrent topics in Susan M. Mniszewski's work include Quantum Computing Algorithms and Architecture (12 papers), Quantum and electron transport phenomena (9 papers) and Quantum Information and Cryptography (9 papers). Susan M. Mniszewski is often cited by papers focused on Quantum Computing Algorithms and Architecture (12 papers), Quantum and electron transport phenomena (9 papers) and Quantum Information and Cryptography (9 papers). Susan M. Mniszewski collaborates with scholars based in United States, Sweden and Italy. Susan M. Mniszewski's co-authors include Christian F. A. Negre, Patricia Fasel, Cliff Joslyn, Phillip D. Stroud, Andy Fulmer, Anders M. N. Niklasson, Enrique R. Vivoni, V. Y. Ivanov, Everett P. Springer and Rafael L. Bras and has published in prestigious journals such as Nature Communications, The Journal of Chemical Physics and Bioinformatics.

In The Last Decade

Susan M. Mniszewski

47 papers receiving 832 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Susan M. Mniszewski United States 16 301 134 130 115 97 49 870
Robert G. Belleman Netherlands 13 96 0.3× 173 1.3× 55 0.4× 76 0.7× 33 0.3× 38 713
Stefan Behnel Germany 4 160 0.5× 203 1.5× 29 0.2× 91 0.8× 7 0.1× 5 852
Kurt Smith United States 3 152 0.5× 60 0.4× 29 0.2× 92 0.8× 7 0.1× 10 726
Craig Citro United States 3 152 0.5× 60 0.4× 29 0.2× 91 0.8× 7 0.1× 4 738
Anna T. Ławniczak Canada 16 94 0.3× 391 2.9× 42 0.3× 81 0.7× 4 0.0× 80 982
Nan Chen China 12 102 0.3× 48 0.4× 58 0.4× 31 0.3× 8 0.1× 60 505
Jan Westerholm Finland 16 57 0.2× 39 0.3× 277 2.1× 76 0.7× 20 0.2× 63 902
R. A. Doney United Kingdom 23 257 0.9× 146 1.1× 147 1.1× 103 0.9× 5 0.1× 99 2.1k
D. A. Aruliah Canada 9 77 0.3× 65 0.5× 110 0.8× 84 0.7× 9 0.1× 17 742
H.A. Larrondo Argentina 19 215 0.7× 154 1.1× 33 0.3× 233 2.0× 6 0.1× 62 1.5k

Countries citing papers authored by Susan M. Mniszewski

Since Specialization
Citations

This map shows the geographic impact of Susan M. Mniszewski'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 Susan M. Mniszewski with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Susan M. Mniszewski more than expected).

Fields of papers citing papers by Susan M. Mniszewski

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Susan M. Mniszewski. 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 Susan M. Mniszewski. The network helps show where Susan M. Mniszewski may publish in the future.

Co-authorship network of co-authors of Susan M. Mniszewski

This figure shows the co-authorship network connecting the top 25 collaborators of Susan M. Mniszewski. A scholar is included among the top collaborators of Susan M. Mniszewski 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 Susan M. Mniszewski. Susan M. Mniszewski 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.
King, Andrew, et al.. (2026). Classical criticality via quantum annealing. Nature Communications. 17(1). 856–856.
2.
Fattebert, Jean‐Luc, Stephen DeWitt, Pablo Seleson, et al.. (2024). Co-design for Particle Applications at Exascale. Computing in Science & Engineering. 26(2). 43–52. 1 indexed citations
3.
Fattebert, Jean‐Luc, Christian F. A. Negre, Jamaludin Mohd‐Yusof, et al.. (2024). Hybrid programming-model strategies for GPU offloading of electronic structure calculation kernels. The Journal of Chemical Physics. 160(12). 4 indexed citations
4.
Slattery, Stuart, Christoph Junghans, Damien Lebrun-Grandié, et al.. (2022). Cabana: A Performance Portable Library forParticle-Based Simulations. The Journal of Open Source Software. 7(72). 4115–4115. 18 indexed citations
5.
Aimone, James B., Prasanna Date, G. A. Fonseca Guerra, et al.. (2022). A review of non-cognitive applications for neuromorphic computing. Neuromorphic Computing and Engineering. 2(3). 32003–32003. 33 indexed citations
6.
Teplukhin, Alexander, Brian K. Kendrick, Susan M. Mniszewski, Sergei Tretiak, & Pavel A. Dub. (2022). Sampling electronic structure quadratic unconstrained binary optimization problems (QUBOs) with Ocean and Mukai solvers. PLoS ONE. 17(2). e0263849–e0263849. 6 indexed citations
7.
Negre, Christian F. A., et al.. (2022). A QUBO formulation for top-τ eigencentrality nodes. PLoS ONE. 17(7). e0271292–e0271292. 3 indexed citations
8.
Babikov, Dmitri, Alexander Teplukhin, Brian K. Kendrick, et al.. (2022). Molecular dynamics on quantum annealers. Scientific Reports. 12(1). 16824–16824. 8 indexed citations
9.
Negre, Christian F. A., et al.. (2020). Quantum isomer search. PLoS ONE. 15(1). e0226787–e0226787. 8 indexed citations
10.
Negre, Christian F. A., et al.. (2020). Detecting multiple communities using quantum annealing on the D-Wave system. PLoS ONE. 15(2). e0227538–e0227538. 49 indexed citations
11.
Mniszewski, Susan M., Christoph Junghans, Arthur F. Voter, Danny Pérez, & Stephan Eidenbenz. (2015). TADSim. ACM Transactions on Modeling and Computer Simulation. 25(3). 1–26. 11 indexed citations
12.
Fairchild, Geoffrey, Kyle S. Hickmann, Susan M. Mniszewski, Sara Y. Del Valle, & James M. Hyman. (2013). Optimizing human activity patterns using global sensitivity analysis. Computational and Mathematical Organization Theory. 20(4). 394–416. 6 indexed citations
13.
Mniszewski, Susan M., et al.. (2008). EpiSimS simulation of a multi-component strategy for pandemic influenza. Spring Simulation Multiconference. 556–563. 32 indexed citations
14.
Mniszewski, Susan M., et al.. (2008). Pandemic simulation of antivirals + school closures: buying time until strain-specific vaccine is available. Computational and Mathematical Organization Theory. 14(3). 209–221. 29 indexed citations
15.
Verspoor, Karin, Judith D. Cohn, Susan M. Mniszewski, & Cliff Joslyn. (2006). A categorization approach to automated ontological function annotation. Protein Science. 15(6). 1544–1549. 45 indexed citations
16.
Stroud, Phillip D., et al.. (2006). Semi-empirical power-law scaling of new infection rate to model epidemic dynamics with inhomogeneous mixing. Mathematical Biosciences. 203(2). 301–318. 39 indexed citations
17.
Vivoni, Enrique R., Susan M. Mniszewski, Patricia Fasel, et al.. (2005). Parallelization of a Fully-Distributed Hydrologic Model using Sub-basin Partitioning. AGU Fall Meeting Abstracts. 2005. 7 indexed citations
18.
Joslyn, Cliff, et al.. (2004). The Gene Ontology Categorizer. Bioinformatics. 20(suppl_1). i169–i177. 62 indexed citations
19.
Beckman, Pete, et al.. (2002). Efficient coupling of parallel applications using PAWS. 37. 215–222. 31 indexed citations
20.
Mniszewski, Susan M., et al.. (1994). Automated Chromatographic Data Interpretation Using an Expert System. Journal of Chromatographic Science. 32(6). 213–218. 9 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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