Chiara Piacentini

19 papers receiving 473 citations

Hit Papers

Proceedings of the National Conference on Artificial Inte...20152026201820222015100200300

Peers

Chiara Piacentini
Comparison fields: 5 of 93
  • Artificial Intelligence 270
  • Computer Vision and Pattern Recognition 132
  • Computer Networks and Communications 74
  • Aerospace Engineering 51
  • Information Systems 41
Replace Georgios Theocharous with:
Georgios Theocharous United States
Haiping Yu China
Daniel J. Mankowitz Israel
Wee Sun Lee Singapore
Shuxin Yang China
Akshat Kumar Singapore
Shishir Kumar Shandilya India
Olivier Buffet France
Lukas Esterle Denmark
Chiara Piacentini relative to Georgios Theocharous United States Georgios Theocharous's profile →
Citations per field
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Georgios Theocharous · 1×
Citations per year

Countries citing papers authored by Chiara Piacentini

Since Specialization
Citations

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

Fields of papers citing papers by Chiara Piacentini

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Chiara Piacentini

This figure shows the co-authorship network connecting the top 25 collaborators of Chiara Piacentini. A scholar is included among the top collaborators of Chiara Piacentini 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 Chiara Piacentini. Chiara Piacentini 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
#WorkIndexed citations
1 3
2 6
3 2
4 2
5 24
6 2
7 5
8 11
9 9
10 14
11 3
12 3
13
International Conference on Automated Planning and Scheduling
41
14 4
15 11
16 3
17 1
18
Proceedings of the National Conference on Artificial Intelligencebreakdown →
315
19 17
20 5

About Chiara Piacentini

Chiara Piacentini is a scholar working on Software, Artificial Intelligence and Computational Theory and Mathematics, having authored 20 papers that have together received 481 indexed citations. Recurring topics across this work include AI-based Problem Solving and Planning (12 papers), Logic, Reasoning, and Knowledge (5 papers) and Constraint Satisfaction and Optimization (5 papers). The work is most often cited by research in Artificial Intelligence (270 citations), Computer Vision and Pattern Recognition (132 citations) and Computational Mathematics (3 citations). Chiara Piacentini has collaborated with scholars based in United Kingdom, Canada and Italy. Frequent co-authors include Maria Fox, Derek Long, J. Christopher Beck, Sara Bernardini, Daniele Magazzeni, Chris Dent, André A. Ciré, Derek Long, Phil Taylor and Fabio Fagnani. Their work appears in journals such as Artificial Intelligence, IEEE Robotics and Automation Letters and Journal of Artificial Intelligence Research.

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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