Vedran Đerek

914 citations
31 papers · 729 · h-index 16

Impact in

Papers in

Vedran Đerek

29 papers receiving 728 citations

Peers

Vedran Đerek
Comparison fields: 5 of 55
  • Cellular and Molecular Neuroscience 403
  • Polymers and Plastics 188
  • Neurology 59
  • Biomedical Engineering 264
  • Electronic, Optical and Magnetic Materials 79
Replace Marie Jakešová with:
Marie Jakešová Sweden
A. Mohr United States
Ludovico Migliaccio Czechia
Moshe David‐Pur Israel
Hao Sheng China
Anton Guimerà‐Brunet Spain
Alexander J. Yeh United States
Isaac P. Clements United States
Nicholas V. Apollo Australia
Zhuolin Xiang Singapore
Vedran Đerek relative to Marie Jakešová Sweden Marie Jakešová's profile →
Citations per field
00.5×
Marie Jakešová · 1×
Citations per year

Countries citing papers authored by Vedran Đerek

Since Specialization
Citations

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

Fields of papers citing papers by Vedran Đerek

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Vedran Đerek, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Vedran Đerek Line = papers co-authored together Vedran Đerek links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 31 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2018122
2 2021120
3 2019100
4 201543
5 202138
6 202035
7 201934
8 201831
9 201831
10 202025
11 201619
12 201418
13 202218
14 201517
15 202117
16 202215
17 202112
18 201810
19 20154
20 20243

About Vedran Đerek

Vedran Đerek is a scholar working on Cellular and Molecular Neuroscience, Biomedical Engineering, Electrical and Electronic Engineering, Materials Chemistry and Polymers and Plastics, having authored 31 papers that have together received 729 indexed citations. Recurring topics across this work include Neuroscience and Neural Engineering (15 papers), Photoreceptor and optogenetics research (10 papers), Silicon Nanostructures and Photoluminescence (8 papers), Conducting polymers and applications (7 papers), Advanced Sensor and Energy Harvesting Materials (5 papers), Nanowire Synthesis and Applications (5 papers), Advanced Memory and Neural Computing (4 papers) and Gold and Silver Nanoparticles Synthesis and Applications (4 papers). The work is most often cited by research in Cellular and Molecular Neuroscience (403 citations), Polymers and Plastics (188 citations), Neurology (59 citations), Biomedical Engineering (264 citations) and Electronic, Optical and Magnetic Materials (79 citations). Vedran Đerek has collaborated with scholars based in Croatia, Sweden and Czechia. Frequent co-authors include Eric Daniel Głowacki, Marie Jakešová, Ludovico Migliaccio, Magnus Berggren, Malin Silverå Ejneby, Maciej Gryszel, Tobias Cramer, David G. Rand, Yael Hanein and Mile Ivanda. Their work appears in journals such as Advanced Materials, Journal of Raman Spectroscopy, Journal of Neural Engineering, Advanced Materials Technologies and IEEE Transactions on Biomedical Engineering.

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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