Marcelo Ladeira
- Artificial Intelligence top 10%
- Information Systems
- Management Science and Operations Research
- Sociology and Political Science
- Computer Networks and Communications
- Co-authors
- Rommel N. CarvalhoPaulo CostaCecília Dias FloresHélder CoelhoRosa María VicariClaus AranhaTetsuya SakuraiJoão Carlos Souza
- Topics
- Metaheuristic Optimization Algorithms Research (6 papers)Evolutionary Algorithms and Applications (6 papers)Data Quality and Management (6 papers)
- Journals
- Artificial Intelligence in MedicineEvolutionary ComputationDementia & Neuropsychologia
In The Last Decade
Marcelo Ladeira
28 papers receiving 151 citations
Peers
Comparison fields: 5 of 73
- Artificial Intelligence 94
- Information Systems 30
- Management Science and Operations Research 22
- Sociology and Political Science 15
- Computer Networks and Communications 12
Countries citing papers authored by Marcelo Ladeira
This map shows the geographic impact of Marcelo Ladeira'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 Marcelo Ladeira with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Marcelo Ladeira more than expected).
Fields of papers citing papers by Marcelo Ladeira
This network shows the impact of papers produced by Marcelo Ladeira. 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 Marcelo Ladeira. The network helps show where Marcelo Ladeira may publish in the future.
Co-authorship network of co-authors of Marcelo Ladeira
This figure shows the co-authorship network connecting the top 25 collaborators of Marcelo Ladeira. A scholar is included among the top collaborators of Marcelo Ladeira 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 Marcelo Ladeira. Marcelo Ladeira is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | 2 | |
| 3 | 0 | |
| 4 | 2 | |
| 5 | 2 | |
| 6 | 1 | |
| 7 | 6 | |
| 8 | 9 | |
| 9 | 3 | |
| 10 | 2 | |
| 11 | 1 | |
| 12 | 0 | |
| 13 | 10 | |
| 14 | 2 | |
| 15 | PR-OWL 2 RL - A Language for Scalable Uncertainty Reasoning on the Semantic Web information. | 0 |
| 16 | 1 | |
| 17 | UMP-ST plug-in: a tool for documenting, maintaining, and evolving probabilistic ontologies | 1 |
| 18 | 16 | |
| 19 | 1 | |
| 20 | 36 |
About Marcelo Ladeira
Marcelo Ladeira is a scholar working on Artificial Intelligence, Management Science and Operations Research and Computer Science Applications, having authored 34 papers that have together received 166 indexed citations. Recurring topics across this work include Metaheuristic Optimization Algorithms Research (6 papers), Evolutionary Algorithms and Applications (6 papers) and Data Quality and Management (6 papers). The work is most often cited by research in Artificial Intelligence (94 citations), Health Informatics (3 citations) and Management Science and Operations Research (22 citations). Marcelo Ladeira has collaborated with scholars based in Brazil, Japan and France. Frequent co-authors include Rommel N. Carvalho, Paulo Costa, Cecília Dias Flores, Hélder Coelho, Rosa María Vicari, Claus Aranha, Tetsuya Sakurai, João Carlos Souza, Maristela Holanda and Márcio Victorino. Their work appears in journals such as Artificial Intelligence in Medicine, Evolutionary Computation and Dementia & Neuropsychologia.
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.