David Guirguis

438 total citations
14 papers, 316 citations indexed

About

David Guirguis is a scholar working on Computational Theory and Mathematics, Civil and Structural Engineering and Artificial Intelligence. According to data from OpenAlex, David Guirguis has authored 14 papers receiving a total of 316 indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Computational Theory and Mathematics, 7 papers in Civil and Structural Engineering and 5 papers in Artificial Intelligence. Recurrent topics in David Guirguis's work include Advanced Multi-Objective Optimization Algorithms (9 papers), Topology Optimization in Engineering (7 papers) and Metaheuristic Optimization Algorithms Research (4 papers). David Guirguis is often cited by papers focused on Advanced Multi-Objective Optimization Algorithms (9 papers), Topology Optimization in Engineering (7 papers) and Metaheuristic Optimization Algorithms Research (4 papers). David Guirguis collaborates with scholars based in Canada, United States and Egypt. David Guirguis's co-authors include Mohamed F. Aly, Cristina H. Amon, David A. Romero, Kazuhiro Saitou, Karim Hamza, William Melek, Jack Beuth, Conrad S. Tucker, Renato Picelli and Markus Olhofer and has published in prestigious journals such as Nature Communications, Journal of Computational Physics and Applied Energy.

In The Last Decade

David Guirguis

14 papers receiving 302 citations

Peers

David Guirguis

CSE

CTM

AE

AI

EEE

Terence Macquart United Kingdom

Marcus Redhe Sweden

Thiagarajan Krishnamurthy United States

Atthaphon Ariyarit Thailand

Vincent K. Maes United Kingdom

Prateek Mittal India

Vahid Keshavarzzadeh United States

Chuang Xiong China

A. Lorenzana Spain

Stuart J. Bates United Kingdom

Terence Macquart United Kingdom

David Guirguis

198 ×1.5

CSE

74 ×0.7

CTM

146 ×1.3

AE

11 ×0.2

AI

21 ×0.3

EEE

Citations per year, relative to David Guirguis David Guirguis (= 1×) peers Terence Macquart

Countries citing papers authored by David Guirguis

Since Specialization

Citations

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

Fields of papers citing papers by David Guirguis

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of David Guirguis

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

All Works

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14 of 14 papers shown

1.

Guirguis, David, Conrad S. Tucker, & Jack Beuth. (2024). Accelerating process development for 3D printing of new metal alloys. Nature Communications. 15(1). 582–582. 17 indexed citations

2.

Guirguis, David, Conrad S. Tucker, & Jack Beuth. (2024). Machine learning for real-time detection of local heat accumulation in metal additive manufacturing. Materials & Design. 241. 112933–112933. 3 indexed citations

3.

Guirguis, David, Nikola Aulig, Renato Picelli, et al.. (2019). Evolutionary Black-Box Topology Optimization: Challenges and Promises. IEEE Transactions on Evolutionary Computation. 24(4). 613–633. 34 indexed citations

4.

Guirguis, David, Miad Nasr, Samantha K. Murray, et al.. (2018). Thermal Management Within Multi-Disciplinary System Design of a Rubik’s-Cube-sized 2kW Power Inverter. 921–926. 6 indexed citations

5.

Guirguis, David, William Melek, & Mohamed F. Aly. (2018). High-resolution non-gradient topology optimization. Journal of Computational Physics. 372. 107–125. 24 indexed citations

6.

Guirguis, David, David A. Romero, & Cristina H. Amon. (2017). Gradient-based multidisciplinary design of wind farms with continuous-variable formulations. Applied Energy. 197. 279–291. 40 indexed citations

7.

Guirguis, David. (2017). Comments on “Evolutionary and GPU computing for topology optimization of structures”. Swarm and Evolutionary Computation. 35. 111–113. 2 indexed citations

8.

Guirguis, David, David A. Romero, & Cristina H. Amon. (2016). Efficient Wind Turbine Micrositing in Large-Scale Wind Farms. 2 indexed citations

9.

Nasr, Miad, David Guirguis, Shahab Poshtkouhi, et al.. (2016). Thermal and electrical co-design of a modular high-density single-phase inverter using wide-bandgap devices. 1350–1357. 10 indexed citations

10.

Guirguis, David, David A. Romero, & Cristina H. Amon. (2016). Toward efficient optimization of wind farm layouts: Utilizing exact gradient information. Applied Energy. 179. 110–123. 72 indexed citations

11.

Guirguis, David & Mohamed F. Aly. (2016). An evolutionary multi-objective topology optimization framework for welded structures. 372–378. 13 indexed citations

12.

Guirguis, David & Mohamed F. Aly. (2016). A derivative-free level-set method for topology optimization. Finite Elements in Analysis and Design. 120. 41–56. 30 indexed citations

13.

Guirguis, David, et al.. (2014). Image Matching Assessment of Attainable Topology via Kriging-Interpolated Level-Sets. 10 indexed citations

14.

Guirguis, David, et al.. (2014). Multi-objective topology optimization of multi-component continuum structures via a Kriging-interpolated level set approach. Structural and Multidisciplinary Optimization. 51(3). 733–748. 53 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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