Petar Simić

402 citations
12 papers · 312 · h-index 7

Impact in

Papers in

Petar Simić

10 papers receiving 289 citations

Peers

Petar Simić
Comparison fields: 5 of 55
  • Nuclear and High Energy Physics 100
  • Computer Vision and Pattern Recognition 89
  • Artificial Intelligence 127
  • Computer Graphics and Computer-Aided Design 7
  • Statistical and Nonlinear Physics 21
Replace Kazuho Watanabe with:
Kazuho Watanabe Japan
Jiaxi Ying Hong Kong
S. C. Phatak India
N. Nefedov Finland
G. Reents Germany
Wahid Bhimji United States
Ramona Wolf Germany
Thomas Schürmann Germany
E.G. Miller United States
Ingo Schmitt Germany
Petar Simić relative to Kazuho Watanabe Japan Kazuho Watanabe's profile →
Citations per field
00.5×9.1×
Kazuho Watanabe · 1×
Citations per year

Countries citing papers authored by Petar Simić

Since Specialization
Citations

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

Fields of papers citing papers by Petar Simić

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 19 scholars most cited alongside Petar Simić, 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 Petar Simić Line = papers co-authored together Petar Simić links everyone, so they are left out of the graph.

All Works

12 of 12 papers shown
#Work
1 199092
2 198553
3 199151
4 199050
5 198643
6 198810
7 20227
8 20242
9 20252
10 20052
11 20240
12 20250

About Petar Simić

Petar Simić is a scholar working on Artificial Intelligence, Reproductive Medicine, Molecular Biology, Computer Networks and Communications and Public Health, Environmental and Occupational Health, having authored 12 papers that have together received 312 indexed citations. Recurring topics across this work include Neural Networks and Applications (4 papers), Glutathione Transferases and Polymorphisms (3 papers), Genomics, phytochemicals, and oxidative stress (3 papers), Ovarian cancer diagnosis and treatment (3 papers), Quantum Chromodynamics and Particle Interactions (2 papers), Black Holes and Theoretical Physics (2 papers), Fuzzy Logic and Control Systems (2 papers) and Particle physics theoretical and experimental studies (2 papers). The work is most often cited by research in Nuclear and High Energy Physics (100 citations), Computer Vision and Pattern Recognition (89 citations), Artificial Intelligence (127 citations), Computer Graphics and Computer-Aided Design (7 citations) and Statistical and Nonlinear Physics (21 citations). Petar Simić has collaborated with scholars based in United States and Serbia. Frequent co-authors include Andrea Giansanti, Ana Savić-Radojević, Vesna Ćorić, Marija Plješa-Ercegovac, Djurdja Jerotić, Tatjana Simić, Vladimir Kanjuh, Zoran Bukumirić, N. Zečević and Tatjana Djukić. Their work appears in journals such as Network Computation in Neural Systems, International Journal of Molecular Sciences, Neural Computation, Physical Review Letters and Medicina.

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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