Armando De Giusti

1.8k total citations · 1 hit paper
48 papers, 892 citations indexed

About

Armando De Giusti is a scholar working on Computer Networks and Communications, Artificial Intelligence and Hardware and Architecture. According to data from OpenAlex, Armando De Giusti has authored 48 papers receiving a total of 892 indexed citations (citations by other indexed papers that have themselves been cited), including 19 papers in Computer Networks and Communications, 19 papers in Artificial Intelligence and 12 papers in Hardware and Architecture. Recurrent topics in Armando De Giusti's work include Parallel Computing and Optimization Techniques (11 papers), Algorithms and Data Compression (10 papers) and Genomics and Phylogenetic Studies (8 papers). Armando De Giusti is often cited by papers focused on Parallel Computing and Optimization Techniques (11 papers), Algorithms and Data Compression (10 papers) and Genomics and Phylogenetic Studies (8 papers). Armando De Giusti collaborates with scholars based in Argentina, Spain and Italy. Armando De Giusti's co-authors include Marcelo Naiouf, Manuel Prieto, Enzo Rucci, Carlos García, Guillermo Botella, Laura Cristina Lanzarini, Claudia Cecilia Russo, Fernando Gustavo Tinetti, Emilio Luque and Juan Carlos Sáez and has published in prestigious journals such as SHILAP Revista de lepidopterología, Future Generation Computer Systems and The Computer Journal.

In The Last Decade

Armando De Giusti

40 papers receiving 800 citations

Hit Papers

Policy Brief: Education during COVID-19 and beyond 2020 2026 2022 2024 2020 100 200 300 400 500
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. Policy Brief: Education during COVID-19 and beyond
    2020 569 citations Armando De Giusti SHILAP Revista de lepidopterología profile →

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Armando De Giusti Argentina 8 315 266 177 129 115 48 892
Alhuseen Omar Alsayed Saudi Arabia 13 490 1.6× 301 1.1× 162 0.9× 87 0.7× 149 1.3× 23 1.1k
Martino Trevisan Italy 15 192 0.6× 215 0.8× 118 0.7× 441 3.4× 315 2.7× 61 1.1k
Marina Blanton United States 18 338 1.1× 448 1.7× 113 0.6× 208 1.6× 813 7.1× 48 1.7k
A Fluck Australia 16 545 1.7× 221 0.8× 22 0.1× 24 0.2× 77 0.7× 88 1.1k
Ali Alammary Saudi Arabia 11 318 1.0× 351 1.3× 25 0.1× 96 0.7× 176 1.5× 24 839
Tatjana Welzer Slovenia 11 66 0.2× 190 0.7× 22 0.1× 116 0.9× 168 1.5× 73 566
Rasheed Abubakar Rasheed Malaysia 9 658 2.1× 289 1.1× 94 0.5× 28 0.2× 77 0.7× 13 1.0k
David Huynh United States 15 36 0.1× 351 1.3× 106 0.6× 179 1.4× 559 4.9× 35 1.4k
Essam Mansour Egypt 15 30 0.1× 299 1.1× 16 0.1× 290 2.2× 198 1.7× 70 748
Brendan Flanagan Japan 16 173 0.5× 288 1.1× 27 0.2× 102 0.8× 218 1.9× 106 777

Countries citing papers authored by Armando De Giusti

Since Specialization
Citations

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

Fields of papers citing papers by Armando De Giusti

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Armando De Giusti. 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 Armando De Giusti. The network helps show where Armando De Giusti may publish in the future.

Co-authorship network of co-authors of Armando De Giusti

This figure shows the co-authorship network connecting the top 25 collaborators of Armando De Giusti. A scholar is included among the top collaborators of Armando De Giusti 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 Armando De Giusti. Armando De Giusti 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.
Naiouf, Marcelo, et al.. (2024). Trends in High Performance Computing and Quantum Computing. SHILAP Revista de lepidopterología. 24(2). e11–e11. 1 indexed citations
2.
Giusti, Armando De. (2023). Transformación Digital en Educación Superior. Posibilidades y Desafíos. SHILAP Revista de lepidopterología. e1–e1. 2 indexed citations
3.
Giusti, Armando De. (2021). Reflexiones sobre Educación y Tecnología Post-Pandemia. SHILAP Revista de lepidopterología. e1–e1. 5 indexed citations
4.
Giusti, Armando De, et al.. (2019). Evolución de un curso inicial de programación a un enfoque multiparadigma. Análisis y resultados. SHILAP Revista de lepidopterología. e01–e01.
5.
Rucci, Enzo, Carlos García, Guillermo Botella, et al.. (2018). SWIFOLD: Smith-Waterman implementation on FPGA with OpenCL for long DNA sequences. BMC Systems Biology. 12(S5). 96–96. 29 indexed citations
6.
Sáez, Juan Carlos, et al.. (2017). On the Interplay Between Throughput, Fairness and Energy Efficiency on Asymmetric Multicore Processors. The Computer Journal. 61(1). 74–94. 4 indexed citations
7.
Rucci, Enzo, Carlos García, Guillermo Botella, et al.. (2015). Smith-Waterman Protein Search with OpenCL on an FPGA. 3. 208–213. 4 indexed citations
8.
Rucci, Enzo, Carlos García, Guillermo Botella, et al.. (2015). An energy‐aware performance analysis of SWIMM: Smith–Waterman implementation on Intel's Multicore and Manycore architectures. Concurrency and Computation Practice and Experience. 27(18). 5517–5537. 14 indexed citations
9.
Giusti, Armando De. (2013). Cloud Computing. Concepts, Technology & Architecture. Dialnet (Universidad de la Rioja). 175–176. 139 indexed citations
10.
Tinetti, Fernando Gustavo, et al.. (2013). Restructuring Fortran legacy applications for parallel computing in multiprocessors. The Journal of Supercomputing. 64(2). 638–659. 2 indexed citations
11.
12.
Rucci, Enzo, et al.. (2011). DNA sequence alignment: hybrid parallel programming on a multicore cluster. El Servicio de Difusión de la Creación Intelectual (National University of La Plata). 183–190. 2 indexed citations
13.
Lanzarini, Laura Cristina, et al.. (2011). Evolutionary multiobjective optimization for emergency medical services. 83–84. 2 indexed citations
14.
Lanzarini, Laura Cristina, et al.. (2009). Particle swarm optimization with oscillation control. 1751–1752. 1 indexed citations
15.
16.
Naiouf, Marcelo, et al.. (2008). Un modelo de arquitectura para el aprendizaje y compartición de conocimiento entre sistemas inteligentes autónomos distribuidos.. 179–188.
17.
Naiouf, Marcelo, et al.. (2008). Mapping Tasks to Processors in Heterogeneous Multiprocessor Architectures: The MATEHa Algorithm. 1900. 85–91. 5 indexed citations
18.
Russo, Claudia Cecilia, et al.. (2006). Image recovery using a new nonlinear adaptive filter based on neural networks. 1. 355–360. 5 indexed citations
19.
Giusti, Armando De, et al.. (2005). Dynamic Load Balance in Parallel Merge Sorting over Homogeneous Clusters. 2. 219–222. 2 indexed citations
20.
Naiouf, Marcelo, et al.. (2003). Parallelization of the N-queens problem. Load unbalance analysis.. El Servicio de Difusión de la Creación Intelectual (National University of La Plata). 2 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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