Nahil Sobh

52 papers receiving 1.9k citations

Nahil Sobh's Hit Papers

Deep learning for topology optimization of 2D metamaterials 2020 · 253 citations
2530+3+6Years since publication100200300

Peers

Nahil Sobh
Comparison fields: 5 of 122
  • Structural Biology 38
  • Automotive Engineering 257
  • Civil and Structural Engineering 432
  • Biophysics 108
  • Mechanical Engineering 636
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Christian J. Cyron Germany
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Zhenkun Lei China
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Citations per year

Countries citing papers authored by Nahil Sobh

Since Specialization
Citations

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

Fields of papers citing papers by Nahil Sobh

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 54 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Mechanical properties of 3D printed polymeric cellular materials with triply periodic minimal surface architectures
Hit paper breakdown →
2017343
2
Deep learning for topology optimization of 2D metamaterials
Hit paper breakdown →
2020253
3 2019162
4 2020157
5 2020149
6 2018128
7 2020107
8 201152
9 202250
10 202143
11 201438
12 202037
13 199032
14 201032
15 202331
16 202029
17 202228
18 201220
19 201120
20 200820

About Nahil Sobh

Nahil Sobh is a scholar working on Atomic and Molecular Physics, and Optics, Mechanics of Materials, Biomedical Engineering, Mechanical Engineering and Computational Mechanics, having authored 54 papers that have together received 2.0k indexed citations. Recurring topics across this work include Digital Holography and Microscopy (13 papers), Advanced Numerical Methods in Computational Mathematics (7 papers), Numerical methods in engineering (5 papers), Advanced Fluorescence Microscopy Techniques (5 papers), Optical Coherence Tomography Applications (4 papers), Optical measurement and interference techniques (4 papers), Matrix Theory and Algorithms (4 papers) and Model Reduction and Neural Networks (4 papers). The work is most often cited by research in Structural Biology (38 citations), Automotive Engineering (257 citations), Civil and Structural Engineering (432 citations), Biophysics (108 citations) and Mechanical Engineering (636 citations). Nahil Sobh has collaborated with scholars based in United States, South Korea and United Arab Emirates. Frequent co-authors include Diab Abueidda, Seid Korić, Iwona Jasiuk, Erman Guleryuz, Jörgen Bergström, Rashid K. Abu Al‐Rub, Mete Bakır, Hüseyin Şehitoğlu, Gabriel Popescu and Umberto Ravaioli. Their work appears in journals such as International Journal for Numerical Methods in Engineering, Materials & Design, Biomedical Optics Express, APL Photonics and Computational Mechanics.

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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