Ruggiero Cavallo

616 citations
22 papers · 327 indexed · h-index 11
Topics
Auction Theory and Applications (22 papers)Game Theory and Applications (9 papers)Experimental Behavioral Economics Studies (7 papers)
Journals
AI MagazineDigital Access to Scholarship at Harvard (DASH) (Harvard University)arXiv (Cornell University)

In The Last Decade

Ruggiero Cavallo

22 papers receiving 302 citations

Peers

Ruggiero Cavallo
Comparison fields: 5 of 33
  • Management Science and Operations Research 267
  • Marketing 122
  • Economics and Econometrics 103
  • Safety Research 63
  • Computer Networks and Communications 60
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Citations per field
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Citations per year

Countries citing papers authored by Ruggiero Cavallo

Since Specialization
Citations

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

Fields of papers citing papers by Ruggiero Cavallo

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Ruggiero Cavallo

This figure shows the co-authorship network connecting the top 25 collaborators of Ruggiero Cavallo. A scholar is included among the top collaborators of Ruggiero Cavallo 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 Ruggiero Cavallo. Ruggiero Cavallo 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 1
2 5
3 8
4 11
5 1
6 20
7 14
8 11
9
Efficient Mechanisms with Dynamic Populations and Dynamic Types
20
10 3
11
Economic hierarchical Q-learning
7
12
Efficient metadeliberation auctions
10
13
Partially-synchronized DEC-MDPs in dynamic mechanism design
3
14 19
15
Social welfare maximization in dynamic strategic decision problems
8
16
Efficient Online Mechanisms for Persistent, Periodically Inaccessible Self-Interested Agents
14
17
Handling self-interest in groups, with minimal cost
1
18 93
19 37
20
TBBL: A Tree-Based Bidding Language for Iterative Combinatorial Exchanges
21

About Ruggiero Cavallo

Ruggiero Cavallo is a scholar working on Management Science and Operations Research, Safety Research and Marketing, having authored 22 papers that have together received 327 indexed citations. Recurring topics across this work include Auction Theory and Applications (22 papers), Game Theory and Applications (9 papers) and Experimental Behavioral Economics Studies (7 papers). The work is most often cited by research in Management Science and Operations Research (267 citations), Marketing (122 citations) and Safety Research (63 citations). Ruggiero Cavallo has collaborated with scholars based in United States, United Kingdom and Spain. Frequent co-authors include David C. Parkes, Satinder Singh, Christopher A. Wilkens, Shaili Jain, Satinder Singh, Sébastien Lahaie, Adam I. Juda, Loizos Michael, Benjamin Lubin and Rad Niazadeh. Their work appears in journals such as AI Magazine, Digital Access to Scholarship at Harvard (DASH) (Harvard University) and arXiv (Cornell University).

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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