Daniel Coca

1.9k total citations
96 papers, 1.2k citations indexed

About

Daniel Coca is a scholar working on Control and Systems Engineering, Statistical and Nonlinear Physics and Artificial Intelligence. According to data from OpenAlex, Daniel Coca has authored 96 papers receiving a total of 1.2k indexed citations (citations by other indexed papers that have themselves been cited), including 26 papers in Control and Systems Engineering, 20 papers in Statistical and Nonlinear Physics and 16 papers in Artificial Intelligence. Recurrent topics in Daniel Coca's work include Control Systems and Identification (18 papers), Neural Networks and Applications (12 papers) and Nonlinear Dynamics and Pattern Formation (11 papers). Daniel Coca is often cited by papers focused on Control Systems and Identification (18 papers), Neural Networks and Applications (12 papers) and Nonlinear Dynamics and Pattern Formation (11 papers). Daniel Coca collaborates with scholars based in United Kingdom, Romania and China. Daniel Coca's co-authors include S.A. Billings, S.A. Billings, Martin Mayfield, Said Munir, Veronica Biga, Peter W. Andrews, Paul J. Gokhale, Viorel Barbu, Roger Hardie and Yuzhu Guo and has published in prestigious journals such as Journal of Geophysical Research Atmospheres, Bioinformatics and PLoS ONE.

In The Last Decade

Daniel Coca

92 papers receiving 1.1k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Daniel Coca United Kingdom 20 254 248 181 159 129 96 1.2k
Antônio José da Silva Neto Brazil 22 245 1.0× 215 0.9× 106 0.6× 143 0.9× 36 0.3× 192 1.6k
John W. Roberts United States 18 190 0.7× 82 0.3× 66 0.4× 95 0.6× 22 0.2× 53 1.6k
Yun Gao China 31 838 3.3× 222 0.9× 510 2.8× 71 0.4× 446 3.5× 165 2.6k
James Hensman United Kingdom 20 275 1.1× 273 1.1× 26 0.1× 511 3.2× 59 0.5× 55 1.7k
Steven Reece United Kingdom 20 127 0.5× 28 0.1× 277 1.5× 440 2.8× 46 0.4× 52 1.6k
Bertrand Michel France 10 35 0.1× 131 0.5× 117 0.6× 295 1.9× 26 0.2× 34 1.3k
Simone Sharma United Kingdom 7 54 0.2× 128 0.5× 55 0.3× 227 1.4× 19 0.1× 7 1.1k
Dimitris Kugiumtzis Greece 28 161 0.6× 174 0.7× 65 0.4× 399 2.5× 648 5.0× 98 2.3k
Yoshito Hirata Japan 24 42 0.2× 325 1.3× 42 0.2× 342 2.2× 503 3.9× 123 1.9k
Philipp Hennig Germany 16 169 0.7× 63 0.3× 36 0.2× 456 2.9× 72 0.6× 48 1.2k

Countries citing papers authored by Daniel Coca

Since Specialization
Citations

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

Fields of papers citing papers by Daniel Coca

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Daniel Coca

This figure shows the co-authorship network connecting the top 25 collaborators of Daniel Coca. A scholar is included among the top collaborators of Daniel Coca 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 Daniel Coca. Daniel Coca 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.
Gutiérrez, Marina, et al.. (2025). Transforming healthcare with chatbots: Uses and applications—A scoping review. Digital Health. 11. 609962886–609962886. 2 indexed citations
2.
Coca, Daniel, et al.. (2025). Stem cell fate decisions: Substates and attractors. Stem Cell Reports. 20(6). 102532–102532. 1 indexed citations
3.
Johnston, Simon A., Veryan Codd, Stephen E. Hamby, et al.. (2024). Aging-related defects in macrophage function are driven by MYC and USF1 transcriptional programs. Cell Reports. 43(4). 114073–114073. 30 indexed citations
4.
Matthews, Brian, Jim W. Hall, Michael Batty, et al.. (2023). DAFNI: a computational platform to support infrastructure systems research. Research Explorer (The University of Manchester). 176(3). 108–116. 3 indexed citations
5.
Wang, Peng, Lyudmila Mihaylova, Said Munir, et al.. (2021). A computationally efficient symmetric diagonally dominant matrix projection-based Gaussian process approach. Signal Processing. 183. 108034–108034. 2 indexed citations
6.
Munir, Said, et al.. (2019). Analysing the performance of low-cost air quality sensors, their drivers, relative benefits and calibration in cities—a case study in Sheffield. Environmental Monitoring and Assessment. 191(2). 94–94. 95 indexed citations
7.
Coca, Daniel, et al.. (2019). Communication Sparsity in Distributed Spiking Neural Network Simulations to Improve Scalability. Frontiers in Neuroinformatics. 13. 19–19. 7 indexed citations
8.
Allison, Thomas F., Andrew J. H. Smith, Konstantinos Anastassiadis, et al.. (2018). Identification and Single-Cell Functional Characterization of an Endodermally Biased Pluripotent Substate in Human Embryonic Stem Cells. Stem Cell Reports. 10(6). 1895–1907. 23 indexed citations
9.
Coca, Daniel, et al.. (2017). A matrix-based approach to solving the inverse Frobenius–Perron problem using sequences of density functions of stochastically perturbed dynamical systems. Communications in Nonlinear Science and Numerical Simulation. 54. 248–266. 11 indexed citations
10.
Billings, S.A., et al.. (2016). Fly Photoreceptors Encode Phase Congruency. PLoS ONE. 11(6). e0157993–e0157993. 7 indexed citations
11.
Barbaric, Ivana, Veronica Biga, Paul J. Gokhale, et al.. (2014). Time-Lapse Analysis of Human Embryonic Stem Cells Reveals Multiple Bottlenecks Restricting Colony Formation and Their Relief upon Culture Adaptation. Stem Cell Reports. 3(1). 142–155. 62 indexed citations
12.
Guo, Ling, Yuzhu Guo, S.A. Billings, & Daniel Coca. (2014). Approximate observability of infinite dimensional bilinear systems using a Volterra series expansion. Systems & Control Letters. 75. 20–26. 1 indexed citations
13.
Billings, S.A., et al.. (2012). Stochastic, Adaptive Sampling of Information by Microvilli in Fly Photoreceptors. Current Biology. 22(15). 1371–1380. 68 indexed citations
14.
Zhao, Yifan, et al.. (2011). SPATIO-TEMPORAL MODELING OF WAVE FORMATION IN AN EXCITABLE CHEMICAL MEDIUM BASED ON A REVISED FITZHUGH–NAGUMO MODEL. International Journal of Bifurcation and Chaos. 21(2). 505–512. 6 indexed citations
15.
Tonge, Peter D., Victor Olariu, Daniel Coca, et al.. (2010). Prepatterning in the Stem Cell Compartment. PLoS ONE. 5(5). e10901–e10901. 18 indexed citations
16.
Wei, Hua‐Liang, Ying Zheng, Yi Pan, et al.. (2009). Model Estimation of Cerebral Hemodynamics Between Blood Flow and Volume Changes: A Data-Based Modeling Approach. IEEE Transactions on Biomedical Engineering. 56(6). 1606–1616. 14 indexed citations
17.
Coca, Daniel, et al.. (2009). A High-Performance Reconfigurable Computing Solution for Peptide Mass Fingerprinting. Methods in molecular biology. 604. 163–185. 1 indexed citations
18.
Gedalin, M., М. А. Балихин, Daniel Coca, Giuseppe Consolini, & R. A. Treumann. (2005). Kinetic description of avalanching systems. Physical Review E. 72(3). 37103–37103. 2 indexed citations
19.
Coca, Daniel & S.A. Billings. (2005). AN ADAPTIVE GPC APPROACH TO LOW-FLOW ANAESTHESIA. IFAC Proceedings Volumes. 38(1). 7–12.
20.
Coca, Daniel & S.A. Billings. (1999). Nonlinear System Identification Using Wavelet Multi-resolution \nModels. White Rose Research Online (University of Leeds, The University of Sheffield, University of York). 31 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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