André Pilastri
- Artificial Intelligence
- Industrial and Manufacturing Engineering top 10%
- Control and Systems Engineering
- Management Information Systems
- Information Systems
- Co-authors
- Paulo CortezCarlos PereiraJoão Manuel R. S. TavaresJosé Carlos MorgadoFilipe RodriguesRui MendesInês RibeiroHelena Rodrigues
- Topics
- Industrial Vision Systems and Defect Detection (6 papers)Imbalanced Data Classification Techniques (5 papers)Machine Learning and Data Classification (4 papers)
In The Last Decade
André Pilastri
22 papers receiving 239 citations
Peers
Comparison fields: 5 of 83
- Artificial Intelligence 83
- Industrial and Manufacturing Engineering 38
- Control and Systems Engineering 27
- Management Information Systems 22
- Information Systems 19
Countries citing papers authored by André Pilastri
This map shows the geographic impact of André Pilastri'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 André Pilastri with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites André Pilastri more than expected).
Fields of papers citing papers by André Pilastri
This network shows the impact of papers produced by André Pilastri. 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 André Pilastri. The network helps show where André Pilastri may publish in the future.
Co-authorship network of co-authors of André Pilastri
This figure shows the co-authorship network connecting the top 25 collaborators of André Pilastri. A scholar is included among the top collaborators of André Pilastri 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 André Pilastri. André Pilastri is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 2 | |
| 3 | 1 | |
| 4 | 9 | |
| 5 | 0 | |
| 6 | 10 | |
| 7 | 1 | |
| 8 | 3 | |
| 9 | 9 | |
| 10 | 14 | |
| 11 | 11 | |
| 12 | 25 | |
| 13 | 2 | |
| 14 | 4 | |
| 15 | 28 | |
| 16 | 70 | |
| 17 | 5 | |
| 18 | 0 | |
| 19 | Reconstruction Algorithms in Compressive Sensing: An Overview | 10 |
| 20 | 3 |
About André Pilastri
André Pilastri is a scholar working on Industrial and Manufacturing Engineering, Radiological and Ultrasound Technology and Artificial Intelligence, having authored 25 papers that have together received 246 indexed citations. Recurring topics across this work include Industrial Vision Systems and Defect Detection (6 papers), Imbalanced Data Classification Techniques (5 papers) and Machine Learning and Data Classification (4 papers). The work is most often cited by research in Industrial and Manufacturing Engineering (38 citations), Health Informatics (5 citations) and Artificial Intelligence (83 citations). André Pilastri has collaborated with scholars based in Portugal, Brazil and India. Frequent co-authors include Paulo Cortez, Carlos Pereira, João Manuel R. S. Tavares, José Carlos Morgado, Filipe Rodrigues, Rui Mendes, Inês Ribeiro, Helena Rodrigues, Rui M. Novais and Rui Sousa. Their work appears in journals such as Sustainability, Applied Soft Computing and Neural Computing and Applications.
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.