Nicole Cusimano

459 total citations
17 papers, 269 citations indexed

About

Nicole Cusimano is a scholar working on Modeling and Simulation, Cardiology and Cardiovascular Medicine and Statistical and Nonlinear Physics. According to data from OpenAlex, Nicole Cusimano has authored 17 papers receiving a total of 269 indexed citations (citations by other indexed papers that have themselves been cited), including 10 papers in Modeling and Simulation, 4 papers in Cardiology and Cardiovascular Medicine and 4 papers in Statistical and Nonlinear Physics. Recurrent topics in Nicole Cusimano's work include Fractional Differential Equations Solutions (7 papers), Cardiac electrophysiology and arrhythmias (4 papers) and COVID-19 epidemiological studies (3 papers). Nicole Cusimano is often cited by papers focused on Fractional Differential Equations Solutions (7 papers), Cardiac electrophysiology and arrhythmias (4 papers) and COVID-19 epidemiological studies (3 papers). Nicole Cusimano collaborates with scholars based in Spain, Australia and United Kingdom. Nicole Cusimano's co-authors include Kevin Burrage, Luca Gerardo‐Giorda, Libin Zhang, Susanne S. Renner, Pamela Burrage, Christopher Drovandi, Brodie Lawson, Ian Turner, Blanca Rodríguez and Félix del Teso and has published in prestigious journals such as PLoS ONE, NeuroImage and Scientific Reports.

In The Last Decade

Nicole Cusimano

15 papers receiving 264 citations

Peers

Nicole Cusimano

CCM

Ling Zhou China

Hardik Joshi India

Fangfang Jiang China

Je-Chiang Tsai Taiwan

Xinglong Li China

Gonzalo Galiano Spain

Huicong Li China

Jorge Duarte Portugal

Shufan Wang China

Silvana Ilie Canada

Ling Zhou China

Nicole Cusimano

123 ×1.3

34 ×0.4

34 ×0.5

CCM

15 ×0.4

57 ×1.8

Citations per year, relative to Nicole Cusimano Nicole Cusimano (= 1×) peers Ling Zhou

Countries citing papers authored by Nicole Cusimano

Since Specialization

Citations

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

Fields of papers citing papers by Nicole Cusimano

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Nicole Cusimano. 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 Nicole Cusimano. The network helps show where Nicole Cusimano may publish in the future.

Co-authorship network of co-authors of Nicole Cusimano

This figure shows the co-authorship network connecting the top 25 collaborators of Nicole Cusimano. A scholar is included among the top collaborators of Nicole Cusimano 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 Nicole Cusimano. Nicole Cusimano is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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17 of 17 papers shown

Cusimano, Nicole, et al.. (2025). UK Biobank MRI data can power the development of generalizable brain clocks: A study of standard ML/DL methodologies and performance analysis on external databases. NeuroImage. 308. 121064–121064. 1 indexed citations

Cusimano, Nicole, et al.. (2023). A Novel Mathematical Approach for Analysis of Integrated Cell–Patient Data Uncovers a 6-Gene Signature Linked to Endocrine Therapy Resistance. Laboratory Investigation. 104(1). 100286–100286. 1 indexed citations

Knopoff, Damián, Nicole Cusimano, Nico Stollenwerk, & Maíra Aguiar. (2022). Spatially Extended SHAR Epidemiological Framework of Infectious Disease Transmission. Computational and Mathematical Methods. 2022. 1–14.

Stollenwerk, Nico, et al.. (2022). Seasonally Forced SIR Systems Applied to Respiratory Infectious Diseases, Bifurcations, and Chaos. Computational and Mathematical Methods. 2022. 1–12. 5 indexed citations

Aguiar, Maíra, et al.. (2021). Critical fluctuations in epidemic models explain COVID-19 post-lockdown dynamics. Scientific Reports. 11(1). 13839–13839. 21 indexed citations

Cusimano, Nicole, Luca Gerardo‐Giorda, & Alessio Gizzi. (2021). A space-fractional bidomain framework for cardiac electrophysiology: 1D alternans dynamics. Chaos An Interdisciplinary Journal of Nonlinear Science. 31(7). 73123–73123. 8 indexed citations

Cusimano, Nicole, Alessio Gizzi, Flavio H. Fenton, Simonetta Filippi, & Luca Gerardo‐Giorda. (2019). Key aspects for effective mathematical modelling of fractional-diffusion in cardiac electrophysiology: A quantitative study. Communications in Nonlinear Science and Numerical Simulation. 84. 105152–105152. 19 indexed citations

Cusimano, Nicole, Félix del Teso, & Luca Gerardo‐Giorda. (2019). Numerical approximations for fractional elliptic equationsviathe method of semigroups. ESAIM Mathematical Modelling and Numerical Analysis. 54(3). 751–774. 5 indexed citations

Cusimano, Nicole, Félix del Teso, Luca Gerardo‐Giorda, & Gianni Pagnini. (2018). Discretizations of the Spectral Fractional Laplacian on General Domains with Dirichlet, Neumann, and Robin Boundary Conditions. SIAM Journal on Numerical Analysis. 56(3). 1243–1272. 30 indexed citations

10.

Lawson, Brodie, Christopher Drovandi, Nicole Cusimano, et al.. (2018). Unlocking data sets by calibrating populations of models to data density: A study in atrial electrophysiology. Science Advances. 4(1). e1701676–e1701676. 57 indexed citations

11.

Cusimano, Nicole & Luca Gerardo‐Giorda. (2018). A space-fractional Monodomain model for cardiac electrophysiology combining anisotropy and heterogeneity on realistic geometries. Journal of Computational Physics. 362. 409–424. 13 indexed citations

12.

Cusimano, Nicole, Kevin Burrage, Ian Turner, & David Kay. (2016). On reflecting boundary conditions for space-fractional equations on a finite interval: Proof of the matrix transfer technique. Applied Mathematical Modelling. 42. 554–565. 11 indexed citations

13.

Drovandi, Christopher, Nicole Cusimano, Brodie Lawson, et al.. (2016). Sampling methods for exploring between-subject variability in cardiac electrophysiology experiments. Journal of The Royal Society Interface. 13(121). 20160214–20160214. 16 indexed citations

14.

Cusimano, Nicole. (2016). FRACTIONAL MODELS IN SPACE FOR DIFFUSIVE PROCESSES IN HETEROGENEOUS MEDIA WITH APPLICATIONS IN CELL MOTILITY AND ELECTRICAL SIGNAL PROPAGATION. Bulletin of the Australian Mathematical Society. 93(3). 518–520.

15.

Cusimano, Nicole, Alfonso Bueno‐Orovio, Ian Turner, & Kevin Burrage. (2015). On the Order of the Fractional Laplacian in Determining the Spatio-Temporal Evolution of a Space-Fractional Model of Cardiac Electrophysiology. PLoS ONE. 10(12). e0143938–e0143938. 32 indexed citations

16.

Cusimano, Nicole, Kevin Burrage, & Pamela Burrage. (2013). Fractional models for the migration of biological cells in complex spatial domains. ANZIAM Journal. 54. 250–250. 6 indexed citations

17.

Cusimano, Nicole, Libin Zhang, & Susanne S. Renner. (2007). Reevaluation of the cox1 Group I Intron in Araceae and Angiosperms Indicates a History Dominated by Loss rather than Horizontal Transfer. Molecular Biology and Evolution. 25(2). 265–276. 44 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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