Miguel Figueroa

1.9k total citations
92 papers, 1.3k citations indexed

About

Miguel Figueroa is a scholar working on Electrical and Electronic Engineering, Artificial Intelligence and Biomedical Engineering. According to data from OpenAlex, Miguel Figueroa has authored 92 papers receiving a total of 1.3k indexed citations (citations by other indexed papers that have themselves been cited), including 37 papers in Electrical and Electronic Engineering, 17 papers in Artificial Intelligence and 17 papers in Biomedical Engineering. Recurrent topics in Miguel Figueroa's work include CCD and CMOS Imaging Sensors (21 papers), Analog and Mixed-Signal Circuit Design (16 papers) and Infrared Target Detection Methodologies (15 papers). Miguel Figueroa is often cited by papers focused on CCD and CMOS Imaging Sensors (21 papers), Analog and Mixed-Signal Circuit Design (16 papers) and Infrared Target Detection Methodologies (15 papers). Miguel Figueroa collaborates with scholars based in Chile, United States and France. Miguel Figueroa's co-authors include C. Diorio, Daniel Hsu, Jorge E. Pezoa, Nadia Nedjah, Gonzalo Carvajal, José Espinoza, Javier Muñoz, L. Jóźwiak, David Hsu and Chris Fisher and has published in prestigious journals such as Physical Review Letters, Nature Communications and NeuroImage.

In The Last Decade

Miguel Figueroa

85 papers receiving 1.2k citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Miguel Figueroa Chile	18	468	299	169	167	164	92	1.3k
Fengbo Ren United States	18	405 0.9×	252 0.8×	294 1.7×	103 0.6×	443 2.7×	48	1.3k
Zhen Fang China	25	696 1.5×	617 2.1×	246 1.5×	297 1.8×	396 2.4×	102	2.0k
Yoshifumi Nishio Japan	16	310 0.7×	278 0.9×	98 0.6×	29 0.2×	145 0.9×	329	1.1k
Ahmet T. Erdogan United Kingdom	23	885 1.9×	253 0.8×	384 2.3×	367 2.2×	253 1.5×	206	2.1k
Hao Shen Germany	14	217 0.5×	142 0.5×	95 0.6×	49 0.3×	259 1.6×	45	1.0k
Miriam Leeser United States	24	742 1.6×	435 1.5×	150 0.9×	761 4.6×	484 3.0×	184	2.1k
Nisar Ahmed United States	19	845 1.8×	399 1.3×	339 2.0×	142 0.9×	123 0.8×	133	1.8k
E.L. Dagless United Kingdom	11	319 0.7×	123 0.4×	238 1.4×	100 0.6×	199 1.2×	52	1.2k
D.M. Hummels United States	15	394 0.8×	406 1.4×	323 1.9×	50 0.3×	221 1.3×	52	1.1k
Ashraf A. M. Khalaf Egypt	26	584 1.2×	403 1.3×	279 1.7×	18 0.1×	820 5.0×	157	2.1k

Countries citing papers authored by Miguel Figueroa

Since Specialization

Citations

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

Fields of papers citing papers by Miguel Figueroa

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Miguel Figueroa

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

All Works

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20 of 20 papers shown

Kfoury, Elie, et al.. (2024). Machine learning controller for data rate management in science DMZ networks. Computer Networks. 242. 110237–110237. 2 indexed citations

Zarkesh-Ha, Payman, et al.. (2023). A CMOS Image Readout Circuit with On-Chip Defective Pixel Detection and Correction. Sensors. 23(2). 934–934. 2 indexed citations

Hernández, C., et al.. (2023). A streaming algorithm and hardware accelerator to estimate the empirical entropy of network flows. Computer Networks. 237. 110035–110035.

Zarkesh-Ha, Payman, et al.. (2022). Motion-Based Object Location on a Smart Image Sensor Using On-Pixel Memory. Sensors. 22(17). 6538–6538. 4 indexed citations

Figueroa, Miguel, et al.. (2022). Guaranteeing Network Reliability to 0-Day Exploits Using Cost-Effective Heterogeneous Node Migration. IEEE Access. 10. 111153–111170. 1 indexed citations

Figueroa, Miguel, et al.. (2022). Survey of Cooperative Advanced Driver Assistance Systems: From a Holistic and Systemic Vision. Sensors. 22(8). 3040–3040. 16 indexed citations

Cariñe, Jaime, et al.. (2021). Post-Measurement Adjustment of the Coincidence Window in Quantum Optics Experiments. IEEE Access. 9. 94010–94016. 1 indexed citations

Figueroa, Miguel, et al.. (2021). A Heterogeneous Hardware Accelerator for Image Classification in Embedded Systems. Sensors. 21(8). 2637–2637. 20 indexed citations

Zarkesh-Ha, Payman, et al.. (2021). Face Recognition on a Smart Image Sensor Using Local Gradients. Sensors. 21(9). 2901–2901. 11 indexed citations

10.

Hernández, C., et al.. (2021). A High-Throughput Hardware Accelerator for Network Entropy Estimation Using Sketches. IEEE Access. 9. 85823–85838. 8 indexed citations

11.

Hernández, C., et al.. (2020). Mining Discriminative K-Mers in DNA Sequences Using Sketches and Hardware Acceleration. IEEE Access. 8. 114715–114732. 6 indexed citations

12.

Godoy, Sebastián E., et al.. (2019). An Instrument for Accurate and Non-Invasive Screening of Skin Cancer Based on Multimodal Imaging. IEEE Access. 7. 176646–176657. 17 indexed citations

13.

Guevara, Pamela, Delphine Duclap, Josselin Houenou, et al.. (2016). Fast Automatic Segmentation of White Matter Streamlines Based on a Multi-Subject Bundle Atlas. Neuroinformatics. 15(1). 71–86. 34 indexed citations

14.

Carvajal, Gonzalo, et al.. (2011). Proceedings of the International Conference on Application-Specific Systems, Architectures and Processors. 18 indexed citations

15.

Carvajal, Gonzalo, Waldo Valenzuela, & Miguel Figueroa. (2007). Subspace-Based Face Recognition in Analog VLSI. Neural Information Processing Systems. 20. 225–232. 5 indexed citations

16.

Figueroa, Miguel, et al.. (2004). On-Chip Compensation of Device-Mismatch Effects in Analog VLSI Neural Networks. Neural Information Processing Systems. 17. 441–448. 8 indexed citations

17.

Rodríguez‐Valverde, Vicente, Rafael Cáliz, J. Mulero Mendoza, et al.. (2004). Segunda actualización del consenso de la Sociedad Española de Reumatología sobre la terapia biológica en la artritis reumatoide. 31(6). 394–401. 5 indexed citations

18.

Figueroa, Miguel, et al.. (2002). Adaptive Quantization and Density Estimation in Silicon. neural information processing systems. 15. 1107–1114. 5 indexed citations

19.

Figueroa, Miguel, et al.. (2002). Field-Programmable Learning Arrays. Neural Information Processing Systems. 15. 1179–1186. 4 indexed citations

20.

Hsu, David, Miguel Figueroa, & C. Diorio. (2000). A Silicon Primitive for Competitive Learning. Neural Information Processing Systems. 713–719. 10 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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