Nisarg Shah

2.8k citations
77 papers · 1.2k indexed · h-index 18

Nisarg Shah

72 papers receiving 1.2k citations

Peers

Nisarg Shah
Comparison fields: 5 of 73
  • Management Science and Operations Research 627
  • General Decision Sciences 49
  • Economics and Econometrics 687
  • Safety Research 123
  • Computer Science Applications 73
Replace Ulle Endriss with:
Ulle Endriss Netherlands
Ioannis Caragiannis Greece
Edith Elkind United Kingdom
Rahul Sami United States
Haris Aziz Australia
Amy Greenwald United States
Nicolas Maudet France
Brendan Lucier United States
Ian A. Kash United States
Piotr Faliszewski Poland
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Citations per field
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Ulle Endriss · 1×
Citations per year

Countries citing papers authored by Nisarg Shah

Since Specialization
Citations

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

Fields of papers citing papers by Nisarg Shah

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

The 25 scholars most cited alongside Nisarg Shah, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Nisarg Shah Line = papers co-authored together Nisarg Shah links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown
#Work
1 20240
2 20234
3 20230
4 20236
5 20233
6 202112
7 20206
8
Group Fairness for Indivisible Goods Allocation
20192
9
Efficient and Thrifty Voting by Any Means Necessary
201911
10 20187
11 20165
12
Truthful univariate estimators
20168
13 201611
14 20151
15
Electing the most probable without eliminating the irrational: voting over intransitive domains
20147
16 20145
17 20130
18 201341
19 201210
20 20114

About Nisarg Shah

Nisarg Shah is a scholar working on Management Science and Operations Research, Economics and Econometrics and General Decision Sciences, having authored 77 papers that have together received 1.2k indexed citations. Recurring topics across this work include Game Theory and Voting Systems (53 papers), Auction Theory and Applications (43 papers), Game Theory and Applications (18 papers), Experimental Behavioral Economics Studies (8 papers), Advanced Bandit Algorithms Research (6 papers), Economic and Environmental Valuation (5 papers), Electoral Systems and Political Participation (5 papers) and Complexity and Algorithms in Graphs (5 papers). The work is most often cited by research in Management Science and Operations Research (627 citations), General Decision Sciences (49 citations) and Economics and Econometrics (687 citations). Nisarg Shah has collaborated with scholars based in United States, Canada and United Kingdom. Frequent co-authors include Ariel D. Procaccia, Ioannis Caragiannis, David C. Parkes, David Kurokawa, Hervé Moulin, Junxing Wang, Ian A. Kash, Rupert Freeman, Vincent Conitzer and Ariel D. Procaccia. Their work appears in journals such as Management Science, Operations Research and Artificial Intelligence.

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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