Eder Miguel

478 total citations
12 papers, 351 citations indexed

About

Eder Miguel is a scholar working on Computational Mechanics, Computer Graphics and Computer-Aided Design and Computer Vision and Pattern Recognition. According to data from OpenAlex, Eder Miguel has authored 12 papers receiving a total of 351 indexed citations (citations by other indexed papers that have themselves been cited), including 5 papers in Computational Mechanics, 5 papers in Computer Graphics and Computer-Aided Design and 3 papers in Computer Vision and Pattern Recognition. Recurrent topics in Eder Miguel's work include Computer Graphics and Visualization Techniques (5 papers), 3D Shape Modeling and Analysis (5 papers) and Modular Robots and Swarm Intelligence (3 papers). Eder Miguel is often cited by papers focused on Computer Graphics and Visualization Techniques (5 papers), 3D Shape Modeling and Analysis (5 papers) and Modular Robots and Swarm Intelligence (3 papers). Eder Miguel collaborates with scholars based in Austria, Italy and Spain. Eder Miguel's co-authors include Bernd Bickel, Miguel Á. Otaduy, Wojciech Matusik, Steve Marschner, Derek Bradley, Bernhard Thomaszewski, Jesús Pérez, Luigi Malomo, Nico Pietroni and Paolo Cignoni and has published in prestigious journals such as Nature Methods, ACM Transactions on Graphics and Computer Graphics Forum.

In The Last Decade

Eder Miguel

12 papers receiving 347 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Eder Miguel Austria	9	138	126	99	69	64	12	351
Mina Konaković Luković United States	6	86 0.6×	298 2.4×	60 0.6×	106 1.5×	51 0.8×	11	464
Andrew O. Sageman‐Furnas Germany	5	83 0.6×	114 0.9×	65 0.7×	33 0.5×	21 0.3×	9	231
Jérémie Dumas United States	11	213 1.5×	189 1.5×	179 1.8×	63 0.9×	23 0.4×	14	632
Jonathan M. Kaldor United States	6	350 2.5×	51 0.4×	267 2.7×	39 0.6×	70 1.1×	8	486
Jituo Li China	12	266 1.9×	23 0.2×	143 1.4×	41 0.6×	113 1.8×	54	389
D.C. Berg Germany	8	54 0.4×	105 0.8×	24 0.2×	65 0.9×	21 0.3×	12	265
Alexandre Kaspar United States	7	78 0.6×	36 0.3×	104 1.1×	35 0.5×	8 0.1×	11	267
Daniel Piker United Kingdom	5	46 0.3×	183 1.5×	39 0.4×	63 0.9×	16 0.3×	8	420
Laurence Boissieux France	14	577 4.2×	45 0.4×	443 4.5×	39 0.6×	230 3.6×	18	778
Jieji Ren China	11	69 0.5×	108 0.9×	19 0.2×	79 1.1×	32 0.5×	36	320

Countries citing papers authored by Eder Miguel

Since Specialization

Citations

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

Fields of papers citing papers by Eder Miguel

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Eder Miguel

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

All Works

Sort: Min cites: Since: Top N: Style:

12 of 12 papers shown

1.

Velicky, Philipp, Eder Miguel, Donglai Wei, et al.. (2023). Dense 4D nanoscale reconstruction of living brain tissue. Nature Methods. 20(8). 1256–1265. 16 indexed citations

2.

Cirio, Gabriel, et al.. (2020). Mixing Yarns and Triangles in Cloth Simulation. Computer Graphics Forum. 39(2). 101–110. 12 indexed citations

3.

Miguel, Eder, et al.. (2018). Toward Estimation of Yarn-Level Cloth Simulation Models. Eurographics. 21–24. 1 indexed citations

4.

Malomo, Luigi, Jesús Pérez, Nico Pietroni, et al.. (2018). FlexMaps. ACM Transactions on Graphics. 37(6). 1–14. 47 indexed citations

5.

Pozzi, María, Eder Miguel, Raphael Deimel, et al.. (2018). Efficient FEM-Based Simulation of Soft Robots Modeled as Kinematic Chains. Use Siena air (University of Siena). 4206–4213. 35 indexed citations

6.

Miguel, Eder, et al.. (2017). CurveUps. ACM Transactions on Graphics. 36(4). 1–12. 78 indexed citations

7.

Miguel, Eder, et al.. (2016). Modeling and Estimation of Energy‐Based Hyperelastic Objects. Computer Graphics Forum. 35(2). 385–396. 16 indexed citations

8.

Miguel, Eder, et al.. (2016). Computational design of stable planar-rod structures. ACM Transactions on Graphics. 35(4). 1–11. 38 indexed citations

9.

Miguel, Eder, Ferdinando Cannella, Matteo Bianchi, et al.. (2015). Characterization of nonlinear finger pad mechanics for tactile rendering. CINECA IRIS Institutial research information system (University of Pisa). 63–68. 13 indexed citations

10.

Miguel, Eder, Andrew Feng, Yuyu Xu, & Ari Shapiro. (2014). Towards Cloth-Manipulating Characters. 3 indexed citations

11.

Miguel, Eder, Rasmus Tamstorf, Derek Bradley, et al.. (2013). Modeling and estimation of internal friction in cloth. ACM Transactions on Graphics. 32(6). 1–10. 7 indexed citations

12.

Miguel, Eder, Derek Bradley, Bernhard Thomaszewski, et al.. (2012). Data‐Driven Estimation of Cloth Simulation Models. Computer Graphics Forum. 31(2pt2). 519–528. 85 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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