Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies
if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the
same subfield and year (this is the minimum needed to enter the top 1%, not the average
within it), or reaches the top citation threshold in at least one of its specific research
topics.
Algorithmic Game Theory
20071.4k citationsNoam Nisan, Noam Nisan et al.Cambridge University Press eBooksprofile →
Peers — A (Enhanced Table)
Peers by citation overlap · career bar shows stage (early→late)
cites ·
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Countries citing papers authored by Jason D. Hartline
Since
Specialization
Citations
This map shows the geographic impact of Jason D. Hartline'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 Jason D. Hartline with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jason D. Hartline more than expected).
Fields of papers citing papers by Jason D. Hartline
This network shows the impact of papers produced by Jason D. Hartline. 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 Jason D. Hartline. The network helps show where Jason D. Hartline may publish in the future.
Co-authorship network of co-authors of Jason D. Hartline
This figure shows the co-authorship network connecting the top 25 collaborators of Jason D. Hartline.
A scholar is included among the top collaborators of Jason D. Hartline 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 Jason D. Hartline. Jason D. Hartline 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
1.
Hartline, Jason D., et al.. (2016). Non-Revelation Mechanism Design.. arXiv (Cornell University).2 indexed citations
2.
Hartline, Jason D., Vasilis Syrgkanis, & Éva Tardos. (2015). No-Regret Learning in Repeated Bayesian Games.. arXiv (Cornell University).1 indexed citations
3.
Haghpanah, Nima & Jason D. Hartline. (2015). Reverse Mechanism Design. 757–758.19 indexed citations
4.
Haghpanah, Nima & Jason D. Hartline. (2014). Reverse Mechanism Design. arXiv (Cornell University).2 indexed citations
Aggarwal, Gagan, Amos Fiat, Andrew V. Goldberg, et al.. (2010). Derandomization of auctions. Games and Economic Behavior. 72(1). 1–11.7 indexed citations
Blum, Avrim & Jason D. Hartline. (2005). Near-optimal online auctions. Symposium on Discrete Algorithms. 1156–1163.65 indexed citations
15.
Guruswami, Venkatesan, Jason D. Hartline, Anna R. Karlin, et al.. (2005). On profit-maximizing envy-free pricing. Symposium on Discrete Algorithms. 1164–1173.143 indexed citations
16.
Hartline, Jason D. & Anna R. Karlin. (2003). Optimization in the private value model: competitive analysis applied to auction design. 224(11). 250–5.6 indexed citations
17.
Goldberg, Andrew V. & Jason D. Hartline. (2003). Competitiveness via consensus. Symposium on Discrete Algorithms. 215–222.36 indexed citations
18.
Deshmukh, Kaustubh, Andrew V. Goldberg, Jason D. Hartline, & Anna R. Karlin. (2002). Truthful and Competitive Double Auctions. Lecture notes in computer science. 361–373.1 indexed citations
Hall, Joseph L., Jason D. Hartline, Anna R. Karlin, Jared Saia, & John Wilkes. (2001). On algorithms for efficient data migration. Symposium on Discrete Algorithms. 620–629.56 indexed citations
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.