Seid Korić

3.2k total citations · 1 hit paper
73 papers, 2.1k citations indexed

About

Seid Korić is a scholar working on Mechanical Engineering, Mechanics of Materials and Materials Chemistry. According to data from OpenAlex, Seid Korić has authored 73 papers receiving a total of 2.1k indexed citations (citations by other indexed papers that have themselves been cited), including 26 papers in Mechanical Engineering, 25 papers in Mechanics of Materials and 16 papers in Materials Chemistry. Recurrent topics in Seid Korić's work include Metallurgical Processes and Thermodynamics (13 papers), Model Reduction and Neural Networks (12 papers) and Aluminum Alloy Microstructure Properties (9 papers). Seid Korić is often cited by papers focused on Metallurgical Processes and Thermodynamics (13 papers), Model Reduction and Neural Networks (12 papers) and Aluminum Alloy Microstructure Properties (9 papers). Seid Korić collaborates with scholars based in United States, Bulgaria and United Arab Emirates. Seid Korić's co-authors include Diab Abueidda, Nahil Sobh, Brian G. Thomas, Erman Guleryuz, Iwona Jasiuk, Junyan He, Hüseyin Şehitoğlu, Lance C. Hibbeler, Vladimir Puzyrev and Ahmed Taha and has published in prestigious journals such as Nano Letters, Journal of Applied Physics and The Journal of Physical Chemistry B.

In The Last Decade

Seid Korić

71 papers receiving 2.1k citations

Hit Papers

Deep learning for topology optimization of 2D metamaterials 2020 2026 2022 2024 2020 50 100 150 200 250
What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

  1. Deep learning for topology optimization of 2D metamaterials
    2020 253 citations Diab Abueidda, Seid Korić et al. Materials & Design profile →

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Seid Korić United States 24 748 542 502 399 302 73 2.1k
Somdatta Goswami United States 18 481 0.6× 1.0k 1.9× 732 1.5× 733 1.8× 361 1.2× 34 2.6k
Hongwei Guo China 15 458 0.6× 1.0k 1.9× 796 1.6× 423 1.1× 345 1.1× 60 2.4k
Khader M. Hamdia Germany 17 537 0.7× 1.1k 2.1× 1.0k 2.1× 346 0.9× 508 1.7× 24 2.7k
Zeliang Liu China 20 858 1.1× 1.1k 2.1× 410 0.8× 378 0.9× 483 1.6× 46 2.5k
Ramin Bostanabad United States 18 585 0.8× 789 1.5× 392 0.8× 313 0.8× 506 1.7× 44 2.0k
Boris Krämer United States 21 687 0.9× 261 0.5× 144 0.3× 496 1.2× 248 0.8× 77 1.6k
Miguel A. Bessa United States 20 744 1.0× 1.5k 2.8× 677 1.3× 316 0.8× 452 1.5× 45 2.5k
S.P. Lim Singapore 24 755 1.0× 1.0k 1.9× 867 1.7× 327 0.8× 205 0.7× 58 2.6k
Adrien Leygue France 26 492 0.7× 787 1.5× 386 0.8× 894 2.2× 160 0.5× 82 2.3k

Countries citing papers authored by Seid Korić

Since Specialization
Citations

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

Fields of papers citing papers by Seid Korić

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Seid Korić

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

All Works

20 of 20 papers shown
1.
Zhong, Weiheng, et al.. (2025). Geometry-informed neural operator transformer for partial differential equations on arbitrary geometries. Computer Methods in Applied Mechanics and Engineering. 451. 118668–118668.
2.
Korić, Seid, et al.. (2025). Toward signed distance function based metamaterial design: Neural operator transformer for forward prediction and diffusion model for inverse design. Computer Methods in Applied Mechanics and Engineering. 446. 118316–118316. 1 indexed citations
3.
Abueidda, Diab, et al.. (2025). Univariate conditional variational autoencoder for morphogenic pattern design in frontal polymerization-based manufacturing. Computer Methods in Applied Mechanics and Engineering. 438. 117848–117848. 3 indexed citations
4.
Ahmed, Farid, et al.. (2025). Virtual sensing-enabled digital twin framework for real-time monitoring of nuclear systems leveraging deep neural operators. npj Materials Degradation. 9(1). 5 indexed citations
5.
Abueidda, Diab, et al.. (2024). Inverse design of short-range order arrangement via neural network. International Journal of Solids and Structures. 309. 113175–113175. 3 indexed citations
6.
Viswanath, Asha, et al.. (2024). Designing a TPMS metamaterial via deep learning and topology optimization. Frontiers in Mechanical Engineering. 10. 5 indexed citations
7.
Mohammed, Ahmed Sameer Khan, et al.. (2023). CRSS determination combining ab-initio framework and Surrogate Neural Networks. International Journal of Plasticity. 162. 103524–103524. 13 indexed citations
8.
Korić, Seid, et al.. (2023). Deep learning operator network for plastic deformation with variable loads and material properties. Engineering With Computers. 40(2). 917–929. 31 indexed citations
9.
He, Junyan, Diab Abueidda, Rashid K. Abu Al‐Rub, Seid Korić, & Iwona Jasiuk. (2023). A deep learning energy-based method for classical elastoplasticity. International Journal of Plasticity. 162. 103531–103531. 48 indexed citations
10.
11.
Korić, Seid & Diab Abueidda. (2022). Data-driven and physics-informed deep learning operators for solution of heat conduction equation with parametric heat source. International Journal of Heat and Mass Transfer. 203. 123809–123809. 74 indexed citations
12.
Huerta, E. A., Asad Khan, Edward Davis, et al.. (2020). Convergence of artificial intelligence and high performance computing on NSF-supported cyberinfrastructure. Journal Of Big Data. 7(1). 36 indexed citations
13.
Abueidda, Diab, Seid Korić, & Nahil Sobh. (2020). Machine learning accelerated topology optimization of nonlinear structures.. arXiv (Cornell University). 1 indexed citations
14.
Abueidda, Diab, et al.. (2020). Deep learning collocation method for solid mechanics: Linear elasticity, hyperelasticity, and plasticity as examples.. arXiv (Cornell University). 1 indexed citations
15.
Sabet, Fereshteh, et al.. (2020). High-Performance Computing Comparison of Implicit and Explicit Nonlinear Finite Element Simulations of Trabecular Bone. Computer Methods and Programs in Biomedicine. 200. 105870–105870. 7 indexed citations
16.
Abueidda, Diab, et al.. (2020). Meshless physics-informed deep learning method for three-dimensional solid mechanics. arXiv (Cornell University). 115 indexed citations
17.
Singh, Akash, Xin Chen, Yumeng Li, Seid Korić, & Erman Guleryuz. (2020). Development of Artificial Neural Network Potential for Graphene. AIAA Scitech 2020 Forum. 3 indexed citations
18.
Abueidda, Diab, et al.. (2020). Deep learning for topology optimization of 2D metamaterials. Materials & Design. 196. 109098–109098. 253 indexed citations breakdown →
19.
Korić, Seid, et al.. (2017). Fracture analysis of multi-osteon cortical bone using XFEM. Computational Mechanics. 62(2). 171–184. 18 indexed citations
20.
Korić, Seid & Brian G. Thomas. (2007). Thermo-mechanical models of steel solidification based on two elastic visco-plastic constitutive laws. Journal of Materials Processing Technology. 197(1-3). 408–418. 76 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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