Igor Melnyk

64 papers receiving 496 citations

Peers

Igor Melnyk
Comparison fields: 5 of 84
  • Statistics, Probability and Uncertainty 32
  • Artificial Intelligence 140
  • Signal Processing 45
  • General Materials Science 13
  • Electrical and Electronic Engineering 183
Replace Aleksey Kudreyko with:
Aleksey Kudreyko Russia
Harish Parthasarathy India
Mohamed Abdelrahman United States
L. Bergman United States
Kai Chen China
Lei Guan China
Arturo Sarmiento-Reyes Mexico
R.A. Kisner United States
Shiyou Yang China
Federico Bizzarri Italy
Igor Melnyk relative to Aleksey Kudreyko Russia Aleksey Kudreyko's profile →
Citations per field
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Citations per year

Countries citing papers authored by Igor Melnyk

Since Specialization
Citations

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

Fields of papers citing papers by Igor Melnyk

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Igor Melnyk, 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 Igor Melnyk Line = papers co-authored together Igor Melnyk links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 82 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201871
2 199955
3 201640
4 201638
5
A simplified process for isotropic texturing of mc-Si
200329
6 201229
7 202226
8 200318
9
Estimating structured vector autoregressive models
201616
10 201314
11 200313
12 202112
13 199911
14 20148
15 20138
16 20058
17
Porous silicon in solar cell structures
20007
18 20097
19
Improved Image Captioning with Adversarial Semantic Alignment.
20186
20 20215

About Igor Melnyk

Igor Melnyk is a scholar working on Electrical and Electronic Engineering, Biomedical Engineering, Artificial Intelligence, Materials Chemistry and Mechanical Engineering, having authored 82 papers that have together received 525 indexed citations. Recurring topics across this work include Laser Design and Applications (22 papers), Plasma Diagnostics and Applications (15 papers), Advanced Sensor Technologies Research (15 papers), Advanced Measurement and Detection Methods (7 papers), Silicon and Solar Cell Technologies (7 papers), Engineering Technology and Methodologies (5 papers), Silicon Nanostructures and Photoluminescence (5 papers) and Multimodal Machine Learning Applications (4 papers). The work is most often cited by research in Statistics, Probability and Uncertainty (32 citations), Artificial Intelligence (140 citations), Signal Processing (45 citations), General Materials Science (13 citations) and Electrical and Electronic Engineering (183 citations). Igor Melnyk has collaborated with scholars based in Ukraine, United States and Poland. Frequent co-authors include Kyongmin Yeo, Arindam Banerjee, Nikunj C. Oza, Bryan Matthews, Stergios I. Roumeliotis, Joel A. Hesch, Hamed Valizadegan, Youssef Mroueh, Inkit Padhi and Shankar Narayanan. Their work appears in journals such as Journal of Computational Physics, Scientific Reports, IEEE Journal on Emerging and Selected Topics in Circuits and Systems, Journal of Artificial Intelligence Research and Solar Energy Materials and Solar Cells.

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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