Ricardo Lima

1.9k total citations · 1 hit paper
85 papers, 1.4k citations indexed

About

Ricardo Lima is a scholar working on Information Systems, Artificial Intelligence and Computational Theory and Mathematics. According to data from OpenAlex, Ricardo Lima has authored 85 papers receiving a total of 1.4k indexed citations (citations by other indexed papers that have themselves been cited), including 31 papers in Information Systems, 24 papers in Artificial Intelligence and 18 papers in Computational Theory and Mathematics. Recurrent topics in Ricardo Lima's work include Service-Oriented Architecture and Web Services (18 papers), Advanced Software Engineering Methodologies (17 papers) and Business Process Modeling and Analysis (13 papers). Ricardo Lima is often cited by papers focused on Service-Oriented Architecture and Web Services (18 papers), Advanced Software Engineering Methodologies (17 papers) and Business Process Modeling and Analysis (13 papers). Ricardo Lima collaborates with scholars based in Brazil, United States and Saudi Arabia. Ricardo Lima's co-authors include Omar Knio, Ignacio E. Grossmann, Márcio Cornélio, Pedro M. Castro, Ana Estanqueiro, Adriano L. I. Oliveira, Augusto Q. Novais, Antonio J. Conejo, Ibrahim Hoteit and Romualdo Salcedo and has published in prestigious journals such as Nature Communications, SHILAP Revista de lepidopterología and European Journal of Operational Research.

In The Last Decade

Ricardo Lima

80 papers receiving 1.3k citations

Hit Papers

A review of hydrogen prod... 2023 2026 2024 2023 50 100 150

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Ricardo Lima Brazil 18 446 290 284 255 171 85 1.4k
Chuan He China 20 1.5k 3.3× 392 1.4× 363 1.3× 141 0.6× 137 0.8× 90 2.0k
Xiuli Wang China 21 968 2.2× 808 2.8× 229 0.8× 51 0.2× 148 0.9× 131 1.7k
George Tsatsaronis Germany 21 151 0.3× 197 0.7× 65 0.2× 145 0.6× 439 2.6× 70 2.1k
Jicheng Liu China 24 694 1.6× 322 1.1× 150 0.5× 37 0.1× 152 0.9× 172 2.0k
Xiaoqing Bai China 19 1.5k 3.5× 586 2.0× 110 0.4× 45 0.2× 69 0.4× 92 1.8k
Cheng Wang China 28 2.6k 5.8× 1.2k 4.2× 269 0.9× 119 0.5× 131 0.8× 141 3.5k
John D. Siirola United States 17 678 1.5× 589 2.0× 97 0.3× 17 0.1× 104 0.6× 38 1.6k
Eric S. Fraga United Kingdom 26 781 1.8× 533 1.8× 146 0.5× 13 0.1× 107 0.6× 100 1.9k
S.A. Khaparde India 25 2.2k 4.8× 893 3.1× 90 0.3× 134 0.5× 195 1.1× 152 2.5k
E.N. Dialynas Greece 21 1.1k 2.5× 441 1.5× 54 0.2× 24 0.1× 186 1.1× 77 1.7k

Countries citing papers authored by Ricardo Lima

Since Specialization
Citations

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

Fields of papers citing papers by Ricardo Lima

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Ricardo Lima

This figure shows the co-authorship network connecting the top 25 collaborators of Ricardo Lima. A scholar is included among the top collaborators of Ricardo Lima 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 Ricardo Lima. Ricardo Lima 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.
Lima, Ricardo, et al.. (2024). An effective hybrid decomposition approach to solve the network-constrained stochastic unit commitment problem in large-scale power systems. SHILAP Revista de lepidopterología. 12. 100085–100085. 3 indexed citations
2.
Lima, Ricardo, et al.. (2024). Addressing extreme weather events for the renewable power-water-heating sectors in Neom, Saudi Arabia. Communications Earth & Environment. 5(1). 1 indexed citations
3.
Lima, Ricardo, et al.. (2023). A review of hydrogen production and supply chain modeling and optimization. International Journal of Hydrogen Energy. 48(37). 13731–13755. 162 indexed citations breakdown →
4.
Conejo, Antonio J., et al.. (2022). Stochastic scheduling of generating units with weekly energy storage: A hybrid decomposition approach. International Journal of Electrical Power & Energy Systems. 145. 108613–108613. 9 indexed citations
5.
Lima, Ricardo, et al.. (2022). Risk-Averse Stochastic Programming vs. Adaptive Robust Optimization: A Virtual Power Plant Application. INFORMS journal on computing. 34(3). 1795–1818. 7 indexed citations
6.
Lima, Ricardo, et al.. (2021). Multiobjective Risk-Aware Path Planning in Uncertain Transient Currents: An Ensemble-Based Stochastic Optimization Approach. IEEE Journal of Oceanic Engineering. 46(4). 1082–1098. 3 indexed citations
7.
Lima, Ricardo, et al.. (2019). Optimal 3D trajectory planning for AUVs using ocean general circulation models. Ocean Engineering. 188. 106266–106266. 11 indexed citations
8.
Lima, Ricardo & Ignacio E. Grossmann. (2018). On the Solution of Nonconvex Cardinality Boolean Quadratic Programming problems. Research Showcase @ Carnegie Mellon University (Carnegie Mellon University).
9.
Lima, Ricardo & Ignacio E. Grossmann. (2018). Computational advances in solving Mixed Integer Linear Programming problems. Figshare. 12 indexed citations
10.
Rebêlo, Henrique, Gary T. Leavens, Mehdi Bagherzadeh, et al.. (2014). AspectJML. Journal of International Crisis and Risk Communication Research. 157–168. 9 indexed citations
11.
Lima, Ricardo, et al.. (2013). REDUCING THE GAP BETWEEN BUSINESS AND INFORMATION SYSTEMS THROUGH COMPLEX EVENT PROCESSING. Computing and Informatics / Computers and Artificial Intelligence. 32(2). 225–250. 3 indexed citations
12.
Lima, Ricardo, Marian G. Marcovecchio, Augusto Q. Novais, & Ignacio E. Grossmann. (2013). On the Computational Studies of Deterministic Global Optimization of Head Dependent Short-Term Hydro Scheduling. IEEE Transactions on Power Systems. 28(4). 4336–4347. 49 indexed citations
13.
Rebêlo, Henrique, et al.. (2012). Enforcing Contracts for Aspect-oriented programs with Annotations, Pointcuts and Advice.. Software Engineering and Knowledge Engineering. 148–153. 1 indexed citations
14.
Lima, Ricardo & Ignacio E. Grossmann. (2011). Computational advances in solving Mixed Integer Linear Programming problems To Professor Sauro Pierucci for leadership in Process Systems Engineering. 1 indexed citations
15.
Rebêlo, Henrique, Roberta Coelho, Ricardo Lima, et al.. (2011). On the interplay of exception handling and design by contract. University of Twente Research Information. 1–6. 5 indexed citations
16.
Lima, Ricardo, et al.. (2009). Modeling and analyzing resource-constrained business processes. TU/e Research Portal. 2824–2830. 9 indexed citations
17.
Lima, Ricardo & Ignacio E. Grossmann. (2008). Optimal synthesis of p‐xylene separation processes based on crystallization technology. AIChE Journal. 55(2). 354–373. 29 indexed citations
18.
19.
Lima, Ricardo, Romualdo Salcedo, & Domingos Barbosa. (2005). SIMOP: Efficient reactive distillation optimization using stochastic optimizers. Chemical Engineering Science. 61(5). 1718–1739. 18 indexed citations
20.
Barreto, Raimundo, et al.. (2004). A formal software synthesis approach for embedded hard real-time systems. 163–168. 1 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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