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.
Adopt: asynchronous distributed constraint optimization with quality guarantees
2004463 citationsPragnesh Jay Modi, Wei‐Min Shen et al.Artificial Intelligenceprofile →
Peers — A (Enhanced Table)
Peers by citation overlap · career bar shows stage (early→late)
cites ·
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Countries citing papers authored by Pragnesh Jay Modi
Since
Specialization
Citations
This map shows the geographic impact of Pragnesh Jay Modi'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 Pragnesh Jay Modi with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Pragnesh Jay Modi more than expected).
Fields of papers citing papers by Pragnesh Jay Modi
This network shows the impact of papers produced by Pragnesh Jay Modi. 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 Pragnesh Jay Modi. The network helps show where Pragnesh Jay Modi may publish in the future.
Co-authorship network of co-authors of Pragnesh Jay Modi
This figure shows the co-authorship network connecting the top 25 collaborators of Pragnesh Jay Modi.
A scholar is included among the top collaborators of Pragnesh Jay Modi 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 Pragnesh Jay Modi. Pragnesh Jay Modi is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Sultanik, Evan A., Pragnesh Jay Modi, & William C. Regli. (2007). On modeling multiagent task scheduling as a distributed constraint optimization problem. International Joint Conference on Artificial Intelligence. 1531–1536.36 indexed citations
4.
Nguyen, Duc‐Toan, et al.. (2007). Intelligent systems demonstration: disaster evacuation support. National Conference on Artificial Intelligence. 1964–1965.4 indexed citations
5.
Nguyen, Duc‐Toan, et al.. (2007). Disaster Evacuation Support.. National Conference on Artificial Intelligence. 1964–1965.3 indexed citations
Modi, Pragnesh Jay, et al.. (2006). A Reference Model for Agent-Based Command and Control Systems. Defense Technical Information Center (DTIC).1 indexed citations
12.
Modi, Pragnesh Jay & Manuela Veloso. (2005). Bumping Strategies for the Private Incremental Multiagent Agreement Problem.. National Conference on Artificial Intelligence. 47–54.3 indexed citations
Tambe, Milind, Wei‐Min Shen, Maja J. Matarić, et al.. (1999). Teamwork in Cyberspace: Using TEAMCORE to Make Agents Team-Ready.23 indexed citations
20.
Knoblock, Craig A., Steven Minton, José Luis Ambite, et al.. (1998). Modeling Web sources for information integration. National Conference on Artificial Intelligence. 211–218.123 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.