Adam Mahdi

1.6k total citations
53 papers, 824 citations indexed

About

Adam Mahdi is a scholar working on Geometry and Topology, Cardiology and Cardiovascular Medicine and Statistical and Nonlinear Physics. According to data from OpenAlex, Adam Mahdi has authored 53 papers receiving a total of 824 indexed citations (citations by other indexed papers that have themselves been cited), including 16 papers in Geometry and Topology, 13 papers in Cardiology and Cardiovascular Medicine and 13 papers in Statistical and Nonlinear Physics. Recurrent topics in Adam Mahdi's work include Advanced Differential Equations and Dynamical Systems (16 papers), Quantum chaos and dynamical systems (11 papers) and Heart Rate Variability and Autonomic Control (6 papers). Adam Mahdi is often cited by papers focused on Advanced Differential Equations and Dynamical Systems (16 papers), Quantum chaos and dynamical systems (11 papers) and Heart Rate Variability and Autonomic Control (6 papers). Adam Mahdi collaborates with scholars based in United Kingdom, United States and Poland. Adam Mahdi's co-authors include Stephen J. Payne, Marco A. F. Pimentel, Maarten De Vos, Fernando Andreotti, Douglas S. Shafer, Seyed Mohammad Mahdi Alavi, Mette S. Olufsen, Andrew J. Majda, John Harlim and Valery G. Romanovski and has published in prestigious journals such as PLoS ONE, Scientific Reports and Journal of Computational Physics.

In The Last Decade

Adam Mahdi

50 papers receiving 797 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Adam Mahdi United Kingdom 15 205 147 123 98 90 53 824
R. W. D. Nickalls United Kingdom 9 101 0.5× 24 0.2× 30 0.2× 56 0.6× 32 0.4× 18 719
Shenzhou Zheng China 12 68 0.3× 48 0.3× 26 0.2× 58 0.6× 41 0.5× 116 776
Riku Klén Finland 16 43 0.2× 10 0.1× 222 1.8× 98 1.0× 27 0.3× 95 1.1k
Karsten Keller Germany 19 93 0.5× 452 3.1× 25 0.2× 132 1.3× 297 3.3× 64 1.3k
Jean‐Marc Ginoux France 15 56 0.3× 215 1.5× 31 0.3× 122 1.2× 53 0.6× 67 781
Joseph D. Skufca United States 12 37 0.2× 222 1.5× 5 0.0× 83 0.8× 62 0.7× 34 1.1k
Da Zhang China 16 121 0.6× 62 0.4× 4 0.0× 165 1.7× 10 0.1× 63 826
Alfonso Delgado-Bonal United States 10 85 0.4× 85 0.6× 3 0.0× 53 0.5× 114 1.3× 17 612
P. P. Kanjilal India 11 265 1.3× 58 0.4× 4 0.0× 190 1.9× 117 1.3× 36 734
Declan G. Bates United Kingdom 25 58 0.3× 75 0.5× 3 0.0× 183 1.9× 19 0.2× 195 2.0k

Countries citing papers authored by Adam Mahdi

Since Specialization
Citations

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

Fields of papers citing papers by Adam Mahdi

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Adam Mahdi

This figure shows the co-authorship network connecting the top 25 collaborators of Adam Mahdi. A scholar is included among the top collaborators of Adam Mahdi 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 Adam Mahdi. Adam Mahdi 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.
Clercq, Djavan De & Adam Mahdi. (2025). Modern computational approaches for rice yield prediction: A systematic review of statistical and machine learning-based methods. Computers and Electronics in Agriculture. 231. 109852–109852. 4 indexed citations
2.
Clercq, Djavan De & Adam Mahdi. (2024). Feasibility of machine learning-based rice yield prediction in India at the district level using climate reanalysis and remote sensing data. Agricultural Systems. 220. 104099–104099. 8 indexed citations
3.
4.
Awais, Muhammad, et al.. (2023). LT-ViT: A Vision Transformer for Multi-Label Chest X-Ray Classification. arXiv (Cornell University). 2565–2569. 5 indexed citations
5.
Lyons, Terry, et al.. (2023). Multimodal Deep Learning Approach to Predicting Neurological Recovery from Coma after Cardiac Arrest. Computing in cardiology. 3 indexed citations
6.
Zarebski, Alexander E., et al.. (2023). Epidemiological waves - Types, drivers and modulators in the COVID-19 pandemic. Heliyon. 9(5). e16015–e16015. 7 indexed citations
7.
Kessler, Sébastien, et al.. (2022). Temporal responses of bumblebee gustatory neurons to sugars. iScience. 25(7). 104499–104499. 7 indexed citations
8.
Armitage, Laura C., Shaun Davidson, Adam Mahdi, et al.. (2022). Diagnosing hypertension in primary care: a retrospective cohort study to investigate the importance of night-time blood pressure assessment. British Journal of General Practice. 73(726). e16–e23. 6 indexed citations
9.
Alavi, Seyed Mohammad Mahdi, Fidel Vila‐Rodriguez, Adam Mahdi, & Stefan M. Goetz. (2022). A formalism for sequential estimation of neural membrane time constant and input–output curve towards selective and closed-loop transcranial magnetic stimulation *. Journal of Neural Engineering. 19(5). 56017–56017. 4 indexed citations
10.
Mahdi, Adam, et al.. (2021). Rigid centres on the center manifold of tridimensional differential systems. Proceedings of the Royal Society of Edinburgh Section A Mathematics. 152(4). 1058–1080.
11.
12.
Armitage, Laura C., Adam Mahdi, Cristian Román, et al.. (2019). Screening for Hypertension in the INpatient Environment(SHINE): a protocol for a prospective study of diagnostic accuracy among adult hospital patients. BMJ Open. 9(12). e033792–e033792. 2 indexed citations
13.
Mahdi, Adam, Anthony A. Birch, Mette S. Olufsen, et al.. (2017). Increased blood pressure variability upon standing up improves reproducibility of cerebral autoregulation indices. Medical Engineering & Physics. 47(1). 151–158. 25 indexed citations
14.
Mahdi, Adam, Nicolette Meshkat, & Seth Sullivant. (2014). Structural Identifiability of Viscoelastic Mechanical Systems. PLoS ONE. 9(2). e86411–e86411. 8 indexed citations
15.
Olufsen, Mette S., et al.. (2014). Modeling Cerebral Blood Flow Velocity During Orthostatic Stress. Annals of Biomedical Engineering. 43(8). 1748–1758. 19 indexed citations
16.
Mahdi, Adam, Jacob Sturdy, Johnny T. Ottesen, & Mette S. Olufsen. (2013). Modeling the Afferent Dynamics of the Baroreflex Control System. PLoS Computational Biology. 9(12). e1003384–e1003384. 33 indexed citations
17.
Mahdi, Adam, et al.. (2013). Center conditions and cyclicity for a family of cubic systems: Computer algebra approach. Mathematics and Computers in Simulation. 87. 55–67. 7 indexed citations
18.
Mahdi, Adam & Clàudìa Valls. (2011). Integrability of the Nosé–Hoover equation. Journal of Geometry and Physics. 61(8). 1348–1352. 8 indexed citations
19.
Edneral, V. F., Adam Mahdi, Valery G. Romanovski, & Douglas S. Shafer. (2011). The center problem on a center manifold in. Nonlinear Analysis. 75(4). 2614–2622. 43 indexed citations
20.
Llibre, Jaume, Adam Mahdi, & Clàudìa Valls. (2011). Polynomial integrability of the Hamiltonian systems with homogeneous potential of degree − 3. Physica D Nonlinear Phenomena. 240(24). 1928–1935. 5 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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