Mario Aguilar

1.7k total citations
28 papers, 1.1k citations indexed

About

Mario Aguilar is a scholar working on Cognitive Neuroscience, Media Technology and Aerospace Engineering. According to data from OpenAlex, Mario Aguilar has authored 28 papers receiving a total of 1.1k indexed citations (citations by other indexed papers that have themselves been cited), including 13 papers in Cognitive Neuroscience, 11 papers in Media Technology and 8 papers in Aerospace Engineering. Recurrent topics in Mario Aguilar's work include Advanced Image Fusion Techniques (10 papers), Infrared Target Detection Methodologies (8 papers) and CCD and CMOS Imaging Sensors (7 papers). Mario Aguilar is often cited by papers focused on Advanced Image Fusion Techniques (10 papers), Infrared Target Detection Methodologies (8 papers) and CCD and CMOS Imaging Sensors (7 papers). Mario Aguilar collaborates with scholars based in United States, United Kingdom and Netherlands. Mario Aguilar's co-authors include Allen M. Waxman, Alexander Toet, J. K. Ijspeert, Thom Carney, Claudio M. Privitera, Leonardo Fernandino, Colin Humphries, Jeffrey R. Binder, Lisa L. Conant and Stanley A. Klein and has published in prestigious journals such as Journal of Neuroscience, Cerebral Cortex and IEEE Transactions on Biomedical Engineering.

In The Last Decade

Mario Aguilar

27 papers receiving 1.0k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Mario Aguilar United States 17 478 360 322 253 169 28 1.1k
Joyce Farrell United States 25 602 1.3× 315 0.9× 696 2.2× 164 0.6× 134 0.8× 95 1.7k
Edward A. Essock United States 23 795 1.7× 385 1.1× 459 1.4× 158 0.6× 102 0.6× 51 1.6k
Thomas Sanocki United States 19 714 1.5× 167 0.5× 825 2.6× 80 0.3× 138 0.8× 60 1.8k
John P. Frisby United Kingdom 23 1.3k 2.7× 210 0.6× 733 2.3× 136 0.5× 237 1.4× 60 1.9k
Hyun Wook Park South Korea 18 333 0.7× 201 0.6× 512 1.6× 24 0.1× 141 0.8× 72 1.1k
V. Tagliasco Italy 14 579 1.2× 82 0.2× 205 0.6× 58 0.2× 147 0.9× 31 1.2k
Yehezkel Yeshurun Israel 17 533 1.1× 105 0.3× 603 1.9× 81 0.3× 56 0.3× 33 1.3k
Miles Hansard United Kingdom 13 206 0.4× 88 0.2× 333 1.0× 127 0.5× 32 0.2× 31 914
Jyrki Rovamo Finland 28 2.9k 6.1× 136 0.4× 373 1.2× 62 0.2× 327 1.9× 93 3.4k
Andrew Glennerster United Kingdom 19 1.0k 2.2× 142 0.4× 297 0.9× 38 0.2× 197 1.2× 54 1.3k

Countries citing papers authored by Mario Aguilar

Since Specialization
Citations

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

Fields of papers citing papers by Mario Aguilar

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Mario Aguilar

This figure shows the co-authorship network connecting the top 25 collaborators of Mario Aguilar. A scholar is included among the top collaborators of Mario Aguilar 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 Mario Aguilar. Mario Aguilar 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.
2.
Connolly, Patrick, Nicola Cellini, Rolando Estrada, et al.. (2018). Closed-Loop Targeted Memory Reactivation during Sleep Improves Spatial Navigation. Frontiers in Human Neuroscience. 12. 28–28. 40 indexed citations
3.
Anderson, Andrew, Jeffrey R. Binder, Leonardo Fernandino, et al.. (2016). Predicting Neural Activity Patterns Associated with Sentences Using a Neurobiologically Motivated Model of Semantic Representation. Cerebral Cortex. 27(9). 4379–4395. 62 indexed citations
4.
Binder, Jeffrey R., Lisa L. Conant, Colin Humphries, et al.. (2016). Toward a brain-based componential semantic representation. Cognitive Neuropsychology. 33(3-4). 130–174. 218 indexed citations
5.
Kasturi, Rangachar, Dmitry B. Goldgof, Gill A. Pratt, et al.. (2014). Performance Evaluation of Neuromorphic-Vision Object Recognition Algorithms. 31. 2401–2406. 8 indexed citations
6.
Privitera, Claudio M., Thom Carney, Stanley A. Klein, & Mario Aguilar. (2013). Analysis of microsaccades and pupil dilation reveals a common decisional origin during visual search. Vision Research. 95. 43–50. 23 indexed citations
7.
Privitera, Claudio M., Laura Renninger, Thom Carney, Stanley A. Klein, & Mario Aguilar. (2010). Pupil dilation during visual target detection. Journal of Vision. 10(10). 3–3. 130 indexed citations
8.
Qian, Ming, Mario Aguilar, Claudio M. Privitera, et al.. (2009). Decision-Level Fusion of EEG and Pupil Features for Single-Trial Visual Detection Analysis. IEEE Transactions on Biomedical Engineering. 56(7). 1929–1937. 32 indexed citations
9.
Barniv, Yair, et al.. (2005). Using EMG to Anticipate Head Motion for Virtual-Environment Applications. IEEE Transactions on Biomedical Engineering. 52(6). 1078–1093. 32 indexed citations
10.
Barniv, Yair, et al.. (2004). Using EMG Signals to Anticipate Head Motion via Recurrent Neural Networks.. 18(5). 199–204. 2 indexed citations
11.
12.
Aguilar, Mario, et al.. (2001). <title>Biologically based sensor fusion for medical imaging</title>. Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE. 4385. 149–158. 18 indexed citations
13.
Fay, David A., Allen M. Waxman, Mario Aguilar, et al.. (2000). Fusion of multi-sensor imagery for night vision: color visualization, target learning and search. 1. TUD3/3–TUD310 vol.1. 69 indexed citations
14.
Aguilar, Mario, et al.. (1999). <title>Field evaluations of dual-band fusion for color night vision</title>. Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE. 3691. 168–175. 17 indexed citations
15.
Waxman, Allen M., et al.. (1998). Opponent-Color Fusion of Multi-Sensor Imagery: Visible, IR and SAR. Defense Technical Information Center (DTIC). 23 indexed citations
16.
Aguilar, Mario, et al.. (1998). <title>Real-time fusion of low-light CCD and uncooled IR imagery for color night vision</title>. Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE. 3364. 124–135. 33 indexed citations
17.
Waxman, Allen M., E. D. Savoye, David A. Fay, et al.. (1997). <title>Electronic imaging aids for night driving: low-light CCD, uncooled thermal IR, and color-fused visible/LWIR</title>. Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE. 2902. 62–73. 11 indexed citations
18.
Toet, Alexander, J. K. Ijspeert, Allen M. Waxman, & Mario Aguilar. (1997). Fusion of visible and thermal imagery improves situational awareness. Displays. 18(2). 85–95. 102 indexed citations
19.
Grossberg, Stephen, et al.. (1997). A Neural Model of Multimodal Adaptive Saccadic Eye Movement Control by Superior Colliculus. Journal of Neuroscience. 17(24). 9706–9725. 69 indexed citations
20.
Aguilar, Mario & William D. Ross. (1994). Incremental Art: A Neural Network System for Recognition by Incremental Feature Extraction. OpenBU/Boston University Institutional Repository (Boston University). 4 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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